docs(prompts): text-only turns no longer end an autonomous run

One tool was doing three jobs (wait on the user, wait on other agents, and
- wrongly - wait for a long-running command), so the driver had to guess which
one an agent meant and used parent_id as the proxy: the root waits for a human,
everyone else waits for agents. That proxy is wrong, since the user can message
any agent from the TUI's agent tree.

Tool identity now carries the intent, and the coordinator records it as a
wait_kind that survives snapshot/restore:

  respond_to_user  -> wait_kind="user",   never auto-resumed (root or not)
  wait_for_agents  -> wait_kind="agents", auto-resumed on a 300s timer
  recovery exhaust -> wait_kind="stalled"

respond_to_user fuses the message and the yield into one call, so there is no
way to answer and then forget to stop - the two-step that gpt-4o-mini skipped
2/2 in live testing. Plain text still renders as before.

Auto-resume is also bounded now: an agent that re-parks after every timeout
burned a model turn every 300s for the rest of the scan (and, since parked
children notify their parent, spammed the parent's inbox on the same cycle).
After _MAX_IDLE_AUTO_RESUMES it stays parked until a real message arrives.

.github/workflows/build-release.yml

@@ -21,6 +21,8 @@ jobs:
             target: macos-x86_64
           - os: ubuntu-22.04
             target: linux-x86_64
+          - os: ubuntu-22.04-arm
+            target: linux-arm64
           - os: windows-latest
             target: windows-x86_64
 
@@ -43,6 +45,20 @@ jobs:
           uv sync --frozen
           uv run pyinstaller strix.spec --noconfirm
 
+          if [[ "${{ runner.os }}" == "Windows" ]]; then
+            dist/strix.exe --version
+          else
+            dist/strix --version
+          fi
+
+          if [[ "${{ matrix.target }}" == "linux-arm64" ]]; then
+            file dist/strix
+            file dist/strix | grep -q "ARM aarch64" || {
+              echo "::error::linux-arm64 artifact is not an ARM aarch64 binary"
+              exit 1
+            }
+          fi
+
           VERSION=$(grep '^version' pyproject.toml | head -1 | sed 's/.*"\(.*\)"/\1/')
           mkdir -p dist/release
 

docs/advanced/configuration.mdx

@@ -19,6 +19,14 @@ Configure Strix using environment variables or a config file.
   Custom API base URL. Also accepts `OPENAI_API_BASE`, `LITELLM_BASE_URL`, or `OLLAMA_API_BASE`.
 </ParamField>
 
+<ParamField path="LLM_EXTRA_HEADERS" type="string">
+  Extra HTTP headers sent on every LLM request, as a JSON object (e.g.
+  `{"X-Feature-Key":"value","X-Tenant":"acme"}`). Useful for OpenAI-compatible
+  gateways that require attribution or routing headers in addition to the bearer
+  token. The bearer token itself still comes from `LLM_API_KEY`. Applies to both
+  the LiteLLM and native OpenAI routing paths.
+</ParamField>
+
 <ParamField path="LLM_TIMEOUT" default="300" type="integer">
   Request timeout in seconds for LLM calls.
 </ParamField>
@@ -55,6 +63,12 @@ affecting the agents that do the actual testing.
   model runs on a different endpoint than the main model.
 </ParamField>
 
+<ParamField path="DEDUPE_LLM_EXTRA_HEADERS" type="string">
+  Optional JSON object of extra HTTP headers sent on every deduplication-model
+  request, e.g. `{"X-Feature-Key":"value"}`. A dedicated dedupe model never
+  inherits `LLM_EXTRA_HEADERS`; set this when its endpoint needs custom headers.
+</ParamField>
+
 <ParamField path="STRIX_DEDUPE_REASONING_EFFORT" type="string">
   Reasoning effort for the deduplication model. Defaults to the model's own
   baseline when unset.

docs/llm-providers/local.mdx

@@ -54,3 +54,20 @@ If you use LM Studio, vLLM, or other runners:
 export STRIX_LLM="openai/local-model"
 export LLM_API_BASE="http://localhost:1234/v1"  # Adjust port as needed
 ```
+
+### Gateways that require custom headers
+
+Some OpenAI-compatible gateways require extra HTTP headers (for attribution or
+tenant routing) alongside the bearer token. Set them with `LLM_EXTRA_HEADERS` as
+a JSON object — they are sent on every request:
+
+```bash
+export STRIX_LLM="openai/your-model"
+export LLM_API_BASE="https://your-gateway.example/v1"
+export LLM_API_KEY="your-bearer-token"          # sent as Authorization: Bearer ...
+export LLM_EXTRA_HEADERS='{"X-Feature-Key":"value","X-Tenant":"acme"}'
+```
+
+For endpoints behind a private CA, point Strix at your certificate bundle with
+the standard `SSL_CERT_FILE=/path/to/ca-bundle.pem` — never disable TLS
+verification against a real endpoint.

docs/usage/cli.mdx

@@ -61,11 +61,28 @@ strix (--target <target> | --target-list <path> | --mount <path>) [options]
   Path to a custom config file (JSON) to use instead of `~/.strix/cli-config.json`.
 </ParamField>
 
-<ParamField path="--max-budget-usd" type="number">
+<ParamField path="--max-budget" type="number">
   Maximum LLM spend in USD for the whole scan, counted cumulatively across the
   root agent and every child agent. The budget is checked after each model
-  response; once the running cost reaches the threshold, the scan stops cleanly
-  with a `stopped` status (not a failure) and the sandbox is torn down.
+  response.
+
+  In non-interactive mode (`-n`), once the running cost reaches the threshold,
+  the scan stops cleanly with a `stopped` status (not a failure) and the sandbox
+  is torn down. Sub-agents are stopped early, at 90% of the budget, reserving
+  the final slice for the root agent to wind down and produce the final report.
+
+  In interactive mode, reaching the budget pauses the scan instead of ending
+  it: every agent parks, and sending any message resumes the scan with the cap
+  extended by the original budget amount. There is no sub-agent reserve in
+  interactive mode.
+
+  As the budget is approached, graduated wrap-up warnings are surfaced to
+  **every** agent so they can finish their work and call their lifecycle tool
+  before the hard stop. The bands sit just below each role's own stop point: the
+  root is warned at **70%, 85% and 95%** (it stops at 100%), while sub-agents are
+  warned at **75%, 80% and 85%** (they stop at the 90% reserve). In interactive
+  mode every agent uses the **70%, 85% and 95%** bands. Percentages shown in the
+  warnings are the real cumulative spend against the full budget.
 
   Must be greater than `0`. Omit the flag for no limit.
 
@@ -84,6 +101,19 @@ strix (--target <target> | --target-list <path> | --mount <path>) [options]
     counts.
 </ParamField>
 
+<ParamField path="--max-turns" type="integer" default="500">
+  Maximum number of turns (one model response plus its tool round) allotted to
+  **each** agent, applied per run. When an agent reaches this limit it is
+  force-stopped.
+
+  As the limit is approached, graduated wrap-up warnings (at 70%, 85% and 95%)
+  are injected into that agent's next model turn so it can prioritise its
+  remaining work and call its lifecycle tool (`finish_scan` for the root agent,
+  `agent_finish` for sub-agents) before the hard stop.
+
+  Must be greater than `0`.
+</ParamField>
+
 ## Examples
 
 ```bash
@@ -99,6 +129,9 @@ strix --target api.example.com --instruction "Focus on IDOR and auth bypass"
 # CI/CD mode
 strix -n --target ./ --scan-mode quick
 
+# Cap cost and per-agent turns
+strix --target https://example.com --max-budget 25 --max-turns 300
+
 # Force diff-scope against a specific base ref
 strix -n --target ./ --scan-mode quick --scope-mode diff --diff-base origin/main
 

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "strix-agent"
-version = "1.3.1"
+version = "1.4.1"
 description = "Open-source AI Hackers for your apps"
 readme = "README.md"
 license = "Apache-2.0"
@@ -220,6 +220,7 @@ ignore = [
 # Stdlib HTTP handler overrides (do_GET/do_POST).
 "strix/interface/auth_cli.py" = ["N802"]
 "tests/test_codex_streaming.py" = ["N802"]
+"tests/test_disable_streaming.py" = ["N802"]
 "tests/test_report_pdf.py" = ["S105", "S106"]
 # Stdlib HTTP handler overrides (do_GET/do_POST) and lazy imports that avoid a
 # circular dependency with strix.telemetry / strix.interface.viewer.report_pdf.

scripts/install.sh

@@ -41,7 +41,7 @@ fi
 
 combo="$os-$arch"
 case "$combo" in
-  linux-x86_64|macos-x86_64|macos-arm64|windows-x86_64)
+  linux-x86_64|linux-arm64|macos-x86_64|macos-arm64|windows-x86_64)
     ;;
   *)
     echo -e "${RED}Unsupported OS/Arch: $os/$arch${NC}"

strix/agents/factory.py

@@ -23,7 +23,7 @@ from strix.tools.agents_graph.tools import (
     send_message_to_agent,
     stop_agent,
     view_agent_graph,
-    wait_for_message,
+    wait_for_agents,
 )
 from strix.tools.finish.tool import finish_scan
 from strix.tools.load_skill.tool import load_skill
@@ -49,6 +49,7 @@ from strix.tools.reporting.tool import (
     get_report,
     list_reports,
 )
+from strix.tools.respond.tool import respond_to_user
 from strix.tools.thinking.tool import think
 from strix.tools.todo.tools import (
     create_todo,
@@ -345,6 +346,10 @@ def _make_shell_configurator(*, chat_completions: bool) -> Any:
     return configure
 
 
+# Tools that hand control away by parking the agent rather than ending the scan.
+_PARKING_TOOLS: frozenset[str] = frozenset({"respond_to_user", "wait_for_agents"})
+
+
 def _lifecycle_tool_completed(tool_name: str, output: Any) -> bool:
     if tool_name == "agent_finish":
         completion_key = "agent_completed"
@@ -363,7 +368,7 @@ def _lifecycle_tool_completed(tool_name: str, output: Any) -> bool:
 
 
 def _wait_tool_parked(tool_name: str, output: Any) -> bool:
-    if tool_name != "wait_for_message" or not isinstance(output, str):
+    if tool_name not in _PARKING_TOOLS or not isinstance(output, str):
         return False
     try:
         parsed = json.loads(output)
@@ -425,7 +430,7 @@ _BASE_TOOLS: tuple[Tool, ...] = (
     scope_rules,
     view_agent_graph,
     send_message_to_agent,
-    wait_for_message,
+    wait_for_agents,
     create_agent,
     stop_agent,
 )
@@ -509,6 +514,9 @@ def build_strix_agent(
         )
 
     agent_tools = [*_EXTRA_TOOLS, *(extra_tools or [])]
+    if interactive:
+        # Yielding to the user is only meaningful when one is attached.
+        agent_tools.append(respond_to_user)
     if is_root:
         tools: list[Tool] = [*_BASE_TOOLS, *agent_tools, finish_scan]
     else:

strix/agents/prompts/system_prompt.jinja

@@ -31,28 +31,26 @@ INTER-AGENT MESSAGES:
 
 {% if interactive %}
 INTERACTIVE BEHAVIOR:
-- You are in an interactive conversation with a user
-- CRITICAL: A message WITHOUT a tool call IMMEDIATELY STOPS your entire execution and waits for user input. This is a HARD SYSTEM CONSTRAINT, not a suggestion.
-  - Statements like "Planning the assessment..." or "I'll now scan..." or "Starting with..." WITHOUT a tool call will HALT YOUR WORK COMPLETELY. The system interprets no-tool-call as "I'm done, waiting for the user."
-  - If you want to plan, call the think tool. If you want to act, call the appropriate tool. There is NO valid reason to output text without a tool call while working on a task.
-  - The ONLY time you may send a message without a tool call is when you are genuinely DONE and presenting final results, or when you NEED the user to answer a question before continuing.
-- EVERY message while working MUST contain exactly one tool call — this is what keeps execution moving. No tool call = execution stops.
-- You may include brief explanatory text BEFORE the tool call
-- Respond naturally when the user asks questions or gives instructions
-- For simple conversation, acknowledgements, or direct questions that you can answer from current context, reply in plain text and stop. Do NOT call think just to prepare wording.
-- If you use a tool to answer a user question (for example list_todos, view_agent_graph, or a file read), then after the tool result arrives, provide the answer in plain text and stop unless the user explicitly asked you to continue working.
-- Never loop through think or other tools just to prepare, polish, confirm, or announce a final answer. Once you know the answer, say it.
-- NEVER send empty messages — if you have nothing to do or say, call the wait_for_message tool
-- If you catch yourself about to describe multiple steps without a tool call, STOP and call the think tool instead
+- You are in an interactive conversation with a user.
+- HOW EXECUTION ENDS: your turn ends ONLY when you make an explicit lifecycle tool call. Plain text NEVER ends your turn and NEVER hands control to the user — text is shown to the user, and then execution continues.
+  - To answer the user and hand control back, call respond_to_user. It delivers your message AND parks you for their reply in one call, so there is no way to answer and then forget to stop. This is the ONLY way to yield to the user.
+  - To wait on another AGENT (a child's report, a peer's reply), call wait_for_agents. That is not a way to reach the user.
+  - To end the whole engagement, call the lifecycle tool: finish_scan (root) or agent_finish (subagent).
+  - A turn that ends with plain text and no tool call does NOT stop you: the system nudges you to continue and will re-run you. Do not rely on going silent to pause — it will not pause you.
+- Answering a user question: put the answer in respond_to_user's message. Do not write the answer as plain text and then fall silent — that does not reach a stopping point, it just triggers a continuation nudge.
+- You may include brief explanatory text before a tool call, and you can narrate while you work — plain text is shown to the user as you go. Narrating is free; respond_to_user is specifically the act of WAITING for the user, so do not call it just to give a status update.
+- Respond naturally when the user asks questions or gives instructions.
+- While actively working on a task, every turn should carry exactly one tool call — use think to plan, the appropriate tool to act, and respond_to_user only when you genuinely need the user.
+- Never loop through think or other tools just to prepare, polish, confirm, or announce an answer. Once you know the answer, send it with respond_to_user.
 {% else %}
 AUTONOMOUS BEHAVIOR:
 - Work autonomously by default
 - You should NOT ask for user input or confirmation - you should always proceed with your task autonomously.
 - Minimize user messaging: avoid redundancy and repetition; consolidate updates into a single concise message
-- NEVER send an empty or blank message. If you have no content to output or need to wait (for user input, subagent results, or any other reason), you MUST call the wait_for_message tool (or another appropriate tool) instead of emitting an empty response.
-- If there is nothing to execute and no user query to answer any more: do NOT send filler/repetitive text — either call wait_for_message or finish your work (subagents: agent_finish; root: finish_scan)
-- While the agent loop is running, almost every output MUST be a tool call. Do NOT send plain text messages; act via tools. If idle, use wait_for_message; when done, use agent_finish (subagents) or finish_scan (root)
-- A text-only turn — even one — IMMEDIATELY ends the scan/run with no report written. The lifecycle tools (``finish_scan`` for root, ``agent_finish`` for subagents) are the ONLY valid way to terminate. If you find yourself wanting to say "Done!" or "Scan complete" without a tool call, call the lifecycle tool instead — the report and termination signal both flow through it.
+- NEVER send an empty or blank message. If you have no content to output or need to wait for subagent results, you MUST call the wait_for_agents tool (or another appropriate tool) instead of emitting an empty response.
+- There is no user attached to this run, so there is nobody to ask and nothing to yield to. If there is nothing left to execute: do NOT send filler/repetitive text — either call wait_for_agents (only if you are genuinely expecting another agent to message you) or finish your work (subagents: agent_finish; root: finish_scan)
+- While the agent loop is running, almost every output MUST be a tool call. Do NOT send plain text messages; act via tools. If waiting on another agent, use wait_for_agents; when done, use agent_finish (subagents) or finish_scan (root)
+- A text-only turn does nothing: it neither ends the run nor yields — it just wastes a turn and forces a retry. The lifecycle tools (``finish_scan`` for root, ``agent_finish`` for subagents) are the ONLY way to terminate, and the report flows through them. If you find yourself wanting to say "Done!" or "Scan complete" without a tool call, call the lifecycle tool instead.
 {% endif %}
 </communication_rules>
 

strix/config/codex.py

@@ -18,12 +18,12 @@ import logging
 import secrets
 import threading
 import time
-import urllib.error
 import urllib.parse
-import urllib.request
 from pathlib import Path
 from typing import TYPE_CHECKING, Any
 
+import requests
+
 
 if TYPE_CHECKING:
     from collections.abc import Iterator
@@ -221,26 +221,19 @@ def _first(query: dict[str, list[str]], key: str) -> str | None:
 
 
 def _post_form(payload: dict[str, str]) -> dict[str, Any]:
-    body = urllib.parse.urlencode(payload).encode("ascii")
-    request = urllib.request.Request(  # noqa: S310 - fixed https OAuth endpoint
-        TOKEN_URL,
-        data=body,
-        headers={
-            "Content-Type": "application/x-www-form-urlencoded",
-            "Accept": "application/json",
-        },
-        method="POST",
-    )
     try:
-        with urllib.request.urlopen(  # noqa: S310  # nosec B310 - fixed https endpoint
-            request, timeout=_TOKEN_TIMEOUT
-        ) as response:
-            data = json.loads(response.read() or b"{}")
-    except urllib.error.HTTPError as exc:
-        detail = exc.read().decode("utf-8", "replace")[:300]
-        raise CodexAuthError("token_http_error", f"HTTP {exc.code}: {detail}") from exc
-    except (urllib.error.URLError, TimeoutError, OSError) as exc:
+        response = requests.post(
+            TOKEN_URL,
+            data=payload,
+            headers={"Accept": "application/json"},
+            timeout=_TOKEN_TIMEOUT,
+        )
+    except requests.RequestException as exc:
         raise CodexAuthError("unavailable", str(exc)) from exc
+    if response.status_code >= 400:
+        detail = response.text[:300]
+        raise CodexAuthError("token_http_error", f"HTTP {response.status_code}: {detail}")
+    data = json.loads(response.content or b"{}")
     if not isinstance(data, dict):
         raise CodexAuthError("bad_response", "token endpoint returned non-object")
     return data

strix/config/models.py

@@ -5,6 +5,7 @@ from __future__ import annotations
 import contextlib
 import inspect
 import os
+import time
 from typing import TYPE_CHECKING, Any
 
 from agents import (
@@ -13,6 +14,8 @@ from agents import (
     set_tracing_disabled,
 )
 from agents.model_settings import ModelSettings
+from agents.models.fake_id import FAKE_RESPONSES_ID
+from agents.models.interface import Model
 from agents.models.multi_provider import MultiProvider
 from agents.models.openai_responses import OpenAIResponsesModel
 from agents.retry import (
@@ -21,6 +24,8 @@ from agents.retry import (
     RetryPolicyContext,
     retry_policies,
 )
+from openai.types.responses import Response, ResponseCompletedEvent
+from openai.types.responses.response_usage import ResponseUsage
 from openai.types.shared import Reasoning
 
 from strix.config import codex
@@ -30,10 +35,17 @@ from strix.config.loader import load_settings
 if TYPE_CHECKING:
     from collections.abc import AsyncIterator
 
-    from agents.models.interface import Model, ModelProvider
+    from agents.agent_output import AgentOutputSchemaBase
+    from agents.handoffs import Handoff
+    from agents.items import ModelResponse, TResponseInputItem, TResponseStreamEvent
+    from agents.models.interface import ModelProvider, ModelTracing
+    from agents.retry import ModelRetryAdvice, ModelRetryAdviceRequest
+    from agents.tool import Tool
+    from agents.usage import Usage
     from openai import AsyncOpenAI
+    from openai.types.responses.response_prompt_param import ResponsePromptParam
 
-    from strix.config.settings import ReasoningEffort, Settings
+    from strix.config.settings import LlmSettings, ReasoningEffort, Settings
 
 
 def request_timeout_extra_args(timeout_s: float | None) -> dict[str, float] | None:
@@ -135,6 +147,124 @@ class _CodexResponsesModel(OpenAIResponsesModel):
                     await result
 
 
+class _NonStreamingModel(Model):
+    """Serve the SDK's streamed run loop from a single non-streaming request.
+
+    Some OpenAI-compatible gateways do not support Server-Sent Events, or
+    deliver them unreliably (dropping structured tool-call deltas, or stalling
+    mid-stream so the whole turn waits out the read timeout). The SDK run loop
+    Strix uses only issues streamed requests, so such a gateway fails every
+    turn. Opt in with ``LLM_DISABLE_STREAMING=true`` to wrap the resolved model
+    so each turn makes one non-streaming ``get_response`` (``stream:false`` on
+    the wire) and the completed result is replayed as a single terminal stream
+    event. The run loop then executes tools and emits run items from that final
+    response exactly as it would for a real stream, so nothing else changes.
+    """
+
+    def __init__(self, inner: Model) -> None:
+        self._inner = inner
+
+    async def close(self) -> None:
+        await self._inner.close()
+
+    def get_retry_advice(self, request: ModelRetryAdviceRequest) -> ModelRetryAdvice | None:
+        return self._inner.get_retry_advice(request)
+
+    async def get_response(
+        self,
+        system_instructions: str | None,
+        input: str | list[TResponseInputItem],  # noqa: A002
+        model_settings: ModelSettings,
+        tools: list[Tool],
+        output_schema: AgentOutputSchemaBase | None,
+        handoffs: list[Handoff],
+        tracing: ModelTracing,
+        *,
+        previous_response_id: str | None,
+        conversation_id: str | None,
+        prompt: ResponsePromptParam | None,
+    ) -> ModelResponse:
+        return await self._inner.get_response(
+            system_instructions,
+            input,
+            model_settings,
+            tools,
+            output_schema,
+            handoffs,
+            tracing,
+            previous_response_id=previous_response_id,
+            conversation_id=conversation_id,
+            prompt=prompt,
+        )
+
+    async def stream_response(
+        self,
+        system_instructions: str | None,
+        input: str | list[TResponseInputItem],  # noqa: A002
+        model_settings: ModelSettings,
+        tools: list[Tool],
+        output_schema: AgentOutputSchemaBase | None,
+        handoffs: list[Handoff],
+        tracing: ModelTracing,
+        *,
+        previous_response_id: str | None,
+        conversation_id: str | None,
+        prompt: ResponsePromptParam | None,
+    ) -> AsyncIterator[TResponseStreamEvent]:
+        response = await self._inner.get_response(
+            system_instructions,
+            input,
+            model_settings,
+            tools,
+            output_schema,
+            handoffs,
+            tracing,
+            previous_response_id=previous_response_id,
+            conversation_id=conversation_id,
+            prompt=prompt,
+        )
+        yield _completed_stream_event(response, getattr(self._inner, "model", None))
+
+
+def _completed_stream_event(
+    model_response: ModelResponse, model_name: object | None
+) -> TResponseStreamEvent:
+    """Wrap a non-streamed ``ModelResponse`` as the terminal event of a stream.
+
+    The run loop builds its authoritative per-turn response solely from the
+    ``response.completed`` event, so a single event carrying the full output
+    and usage is all it needs.
+    """
+    response = Response(
+        id=model_response.response_id or FAKE_RESPONSES_ID,
+        created_at=time.time(),
+        model=str(model_name) if model_name else "",
+        object="response",
+        output=list(model_response.output),
+        tool_choice="auto",
+        tools=[],
+        parallel_tool_calls=False,
+        usage=_response_usage(model_response.usage),
+    )
+    return ResponseCompletedEvent(
+        response=response,
+        sequence_number=0,
+        type="response.completed",
+    )
+
+
+def _response_usage(usage: Usage | None) -> ResponseUsage | None:
+    if usage is None:
+        return None
+    return ResponseUsage(
+        input_tokens=usage.input_tokens,
+        output_tokens=usage.output_tokens,
+        total_tokens=usage.total_tokens,
+        input_tokens_details=usage.input_tokens_details,
+        output_tokens_details=usage.output_tokens_details,
+    )
+
+
 class StrixProvider(MultiProvider):
     """Route any non-OpenAI prefix through LiteLLM with the prefix preserved,
     so users type ``deepseek/deepseek-chat`` rather than
@@ -159,14 +289,21 @@ class StrixProvider(MultiProvider):
         return self._get_fallback_provider("litellm"), original_model_name
 
     def get_model(self, model_name: str | None) -> Model:
+        llm = load_settings().llm
         slug = codex.subscription_model(model_name)
         if slug:
+            # The ChatGPT subscription backend is always streamed; it has no
+            # non-streaming mode to fall back to, so LLM_DISABLE_STREAMING
+            # does not apply here.
             return _CodexResponsesModel(
                 slug,
                 codex.get_subscription_client(),
-                reasoning_effort=load_settings().llm.reasoning_effort,
+                reasoning_effort=llm.reasoning_effort,
             )
-        return super().get_model(model_name)
+        model = super().get_model(model_name)
+        if llm.disable_streaming:
+            return _NonStreamingModel(model)
+        return model
 
 
 DEFAULT_MODEL_RETRY = ModelRetrySettings(
@@ -243,6 +380,7 @@ def configure_sdk_model_defaults(settings: Settings) -> None:
         set_default_openai_api("chat_completions")
     else:
         set_default_openai_api("responses")
+    _configure_extra_headers(llm)
 
 
 def _mirror_api_key_to_provider_env(model_name: str | None, api_key: str) -> None:
@@ -277,6 +415,51 @@ def _configure_litellm_compatibility() -> None:
     litellm.suppress_debug_info = True
 
     _register_litellm_cost_callback()
+    _install_openrouter_stream_cost_capture()
+
+
+def _install_openrouter_stream_cost_capture() -> None:
+    """Preserve OpenRouter's per-stream cost, which LiteLLM drops when streaming.
+
+    OpenRouter reports the real charge in ``usage.cost`` of the final stream
+    chunk, but LiteLLM rebuilds streamed responses from token-only fields and
+    discards it (its non-streamed path stashes the cost in hidden params; the
+    streaming path does not). Every scan streams, so without this the cost is
+    lost and Strix falls back to a cost-map estimate that is missing entirely
+    for new models (e.g. kimi-k3), reporting $0. Subclass the OpenRouter
+    streaming handler to record the cost keyed by response id so the cost
+    callback can recover the exact charge for the matching rebuilt response.
+    """
+    import litellm
+    from litellm.llms.openrouter.chat.transformation import (
+        OpenRouterChatCompletionStreamingHandler,
+        OpenrouterConfig,
+    )
+
+    from strix.report.state import streamed_openrouter_costs
+
+    class _StrixOpenRouterStreamingHandler(OpenRouterChatCompletionStreamingHandler):
+        def chunk_parser(self, chunk: dict[str, Any]) -> Any:
+            stream = super().chunk_parser(chunk)
+            streamed_openrouter_costs.remember(
+                chunk.get("id") or getattr(stream, "id", None), chunk.get("usage")
+            )
+            return stream
+
+    class _StrixOpenrouterConfig(OpenrouterConfig):
+        def get_model_response_iterator(
+            self, streaming_response: Any, sync_stream: bool, json_mode: bool | None = False
+        ) -> Any:
+            return _StrixOpenRouterStreamingHandler(
+                streaming_response=streaming_response,
+                sync_stream=sync_stream,
+                json_mode=json_mode,
+            )
+
+    # LiteLLM's provider-config factory reads litellm.OpenrouterConfig at call
+    # time, so overriding the attribute is enough for the subclass to take
+    # effect. (type: ignore — mypy rejects reassigning a class attribute.)
+    litellm.OpenrouterConfig = _StrixOpenrouterConfig  # type: ignore[misc]
 
 
 _OPENROUTER_ATTRIBUTION_HEADERS = {
@@ -302,6 +485,43 @@ def _configure_openrouter_attribution(model_name: str | None) -> None:
     litellm.headers = {**existing, **_OPENROUTER_ATTRIBUTION_HEADERS}  # type: ignore[assignment]
 
 
+def _configure_extra_headers(llm: LlmSettings) -> None:
+    """Send user-provided default headers on every LLM request.
+
+    Some OpenAI-compatible endpoints require extra HTTP headers (e.g. request
+    attribution or tenant routing) alongside the bearer token. Users supply
+    them via ``LLM_EXTRA_HEADERS``; they are applied to both routing paths:
+    the LiteLLM route (``litellm.headers``) and the SDK-native OpenAI route
+    (a default client carrying ``default_headers``), so they take effect
+    regardless of the ``STRIX_LLM`` prefix.
+    """
+    headers = llm.extra_headers
+    if not headers:
+        return
+    _merge_litellm_headers(headers)
+    _register_openai_client_with_headers(llm, headers)
+
+
+def _merge_litellm_headers(headers: dict[str, str]) -> None:
+    import litellm
+
+    current: object = litellm.headers
+    existing: dict[str, str] = current if isinstance(current, dict) else {}
+    litellm.headers = {**existing, **headers}  # type: ignore[assignment]
+
+
+def _register_openai_client_with_headers(llm: LlmSettings, headers: dict[str, str]) -> None:
+    from agents import set_default_openai_client
+    from openai import AsyncOpenAI
+
+    client = AsyncOpenAI(
+        api_key=llm.api_key or "not-needed",
+        base_url=llm.api_base,
+        default_headers=dict(headers),
+    )
+    set_default_openai_client(client, use_for_tracing=False)
+
+
 def _register_litellm_cost_callback() -> None:
     import litellm
 
@@ -429,3 +649,45 @@ def is_known_openai_bare_model(model_name: str) -> bool:
         return False
     entry = litellm.model_cost.get(name)
     return bool(entry and entry.get("litellm_provider") == "openai")
+
+
+def is_claude_model(model_name: str) -> bool:
+    return "claude" in (model_name or "").strip().lower()
+
+
+def is_bedrock_route(model_name: str) -> bool:
+    name = (model_name or "").strip().lower()
+    return name.startswith("bedrock/") or "anthropic." in name
+
+
+def _prompt_cache_name_candidates(model_name: str) -> list[str]:
+    # LiteLLM's model map keys the same model under several names; strip the
+    # route prefix, then leading dotted segments (region, provider).
+    name = (model_name or "").strip().lower()
+    for prefix in ("litellm/", "bedrock/"):
+        if name.startswith(prefix):
+            name = name[len(prefix) :]
+            break
+    candidates = [name]
+    rest = name
+    while "." in rest:
+        rest = rest.split(".", 1)[1]
+        candidates.append(rest)
+    return candidates
+
+
+def bedrock_route_supports_prompt_caching(model_name: str) -> bool:
+    # Bedrock rejects the cache marker for models LiteLLM's map doesn't
+    # recognise as cache-capable, so callers withhold it unless confirmed here.
+    import litellm
+
+    checker = getattr(getattr(litellm, "utils", None), "supports_prompt_caching", None)
+    for cand in _prompt_cache_name_candidates(model_name):
+        if checker is not None:
+            with contextlib.suppress(Exception):
+                if checker(cand):
+                    return True
+        entry = litellm.model_cost.get(cand)
+        if entry and entry.get("supports_prompt_caching"):
+            return True
+    return False

strix/config/settings.py

@@ -35,11 +35,23 @@ class LlmSettings(BaseSettings):
             "OLLAMA_API_BASE",
         ),
     )
+    extra_headers: dict[str, str] | None = Field(
+        default=None,
+        alias="LLM_EXTRA_HEADERS",
+    )
     reasoning_effort: ReasoningEffort = Field(default="high", alias="STRIX_REASONING_EFFORT")
     force_required_tool_choice: bool = Field(
         default=False,
         alias="STRIX_FORCE_REQUIRED_TOOL_CHOICE",
     )
+    prompt_cache: bool = Field(
+        default=True,
+        alias="STRIX_PROMPT_CACHE",
+    )
+    disable_streaming: bool = Field(
+        default=False,
+        alias="LLM_DISABLE_STREAMING",
+    )
     timeout: int = Field(default=300, alias="LLM_TIMEOUT")
 
 
@@ -53,6 +65,10 @@ class DedupeSettings(BaseSettings):
     )
     api_key: str | None = Field(default=None, alias="DEDUPE_LLM_API_KEY")
     api_base: str | None = Field(default=None, alias="DEDUPE_LLM_API_BASE")
+    extra_headers: dict[str, str] | None = Field(
+        default=None,
+        alias="DEDUPE_LLM_EXTRA_HEADERS",
+    )
 
 
 class ContextSettings(BaseSettings):

strix/core/agents.py

@@ -14,13 +14,20 @@ from strix.core.sessions import session_write_lock
 
 
 if TYPE_CHECKING:
+    from collections.abc import Callable
+
     from agents.items import TResponseInputItem
     from agents.memory import Session
 
 
 logger = logging.getLogger(__name__)
 
-Status = Literal["running", "waiting", "completed", "stopped", "crashed", "failed"]
+Status = Literal["running", "waiting", "completed", "stopped", "crashed", "failed", "budget_paused"]
+
+# Why an agent parked. The user can message any agent, so this - not the agent's
+# position in the tree - decides whether waiting is bounded: only an agent waiting
+# on other agents is re-checked on a timer.
+WaitKind = Literal["user", "agents", "stalled"]
 
 
 @dataclass(slots=True)
@@ -30,6 +37,8 @@ class AgentRuntime:
     stream: Any | None = None
     interrupt_on_message: bool = False
     wake: asyncio.Event = field(default_factory=asyncio.Event)
+    mailbox: list[dict[str, Any]] = field(default_factory=list)
+    user_wake_required: bool = False
 
 
 class AgentCoordinator:
@@ -42,11 +51,17 @@ class AgentCoordinator:
         self.metadata: dict[str, dict[str, Any]] = {}
         self.pending_counts: dict[str, int] = {}
         self.errors: dict[str, str] = {}
+        self.recovery_counts: dict[str, int] = {}
+        self.idle_resume_counts: dict[str, int] = {}
+        self.wait_kinds: dict[str, WaitKind] = {}
         self.runtimes: dict[str, AgentRuntime] = {}
         self._lock = asyncio.Lock()
         self._snapshot_path: Path | None = None
         self.is_shutting_down = False
         self._budget_stopped = False
+        self._reserve_stopped = False
+        self._budget_paused = False
+        self._extend_budget: Callable[[], None] | None = None
 
     def set_snapshot_path(self, path: Path) -> None:
         self._snapshot_path = path
@@ -65,6 +80,71 @@ class AgentCoordinator:
             for runtime in self.runtimes.values():
                 runtime.wake.set()
 
+    @property
+    def reserve_stopped(self) -> bool:
+        return self._reserve_stopped
+
+    @property
+    def budget_paused(self) -> bool:
+        return self._budget_paused
+
+    def set_budget_extender(self, extend: Callable[[], None]) -> None:
+        self._extend_budget = extend
+
+    async def pause_for_budget(self, agent_id: str) -> None:
+        async with self._lock:
+            self._budget_paused = True
+        await self.set_status(agent_id, "budget_paused")
+
+    async def resume_from_budget_pause(self, *, exclude: str | None = None) -> None:
+        async with self._lock:
+            if not self._budget_paused:
+                return
+            self._budget_paused = False
+            paused = [aid for aid, status in self.statuses.items() if status == "budget_paused"]
+        if self._extend_budget is not None:
+            self._extend_budget()
+        for aid in paused:
+            await self.set_status(aid, "waiting")
+            if aid != exclude:
+                await self.send(
+                    aid,
+                    {
+                        "from": "system",
+                        "type": "budget_extended",
+                        "content": (
+                            "[Budget] The user extended the scan budget \u2014 continue your "
+                            "current task."
+                        ),
+                    },
+                )
+
+    async def reset_budget_stops(
+        self,
+        *,
+        budget_stopped: bool,
+        reserve_stopped: bool,
+        budget_paused: bool = False,
+    ) -> None:
+        async with self._lock:
+            self._budget_stopped = budget_stopped
+            self._reserve_stopped = reserve_stopped
+            if not budget_paused:
+                self._budget_paused = False
+                for aid, status in self.statuses.items():
+                    if status == "budget_paused":
+                        self.statuses[aid] = "waiting"
+        await self._maybe_snapshot()
+
+    async def claim_reserve_notification(self) -> str | None:
+        async with self._lock:
+            if self._reserve_stopped:
+                return None
+            self._reserve_stopped = True
+            for runtime in self.runtimes.values():
+                runtime.wake.set()
+            return next((aid for aid, parent in self.parent_of.items() if parent is None), None)
+
     async def register(
         self,
         agent_id: str,
@@ -109,11 +189,58 @@ class AgentCoordinator:
             if agent_id in self.statuses:
                 self.statuses[agent_id] = "running"
                 self.errors.pop(agent_id, None)
+                self.wait_kinds.pop(agent_id, None)
+                self.runtimes.setdefault(agent_id, AgentRuntime()).user_wake_required = False
         await self._maybe_snapshot()
 
-    async def park_waiting(self, agent_id: str) -> None:
+    async def park_waiting(self, agent_id: str, *, wait_kind: WaitKind) -> None:
+        """Park an agent, recording what it is waiting on so the driver can time it."""
+        async with self._lock:
+            if agent_id in self.statuses:
+                self.wait_kinds[agent_id] = wait_kind
         await self.set_status(agent_id, "waiting")
 
+    async def wait_kind_of(self, agent_id: str) -> WaitKind | None:
+        async with self._lock:
+            return self.wait_kinds.get(agent_id)
+
+    async def record_recovery(self, agent_id: str) -> int:
+        """Count a turn that ended without a lifecycle tool call; return the new total.
+
+        Persisted so a resumed agent cannot earn a fresh nudge budget on every
+        auto-resume and loop forever.
+        """
+        async with self._lock:
+            count = self.recovery_counts.get(agent_id, 0) + 1
+            self.recovery_counts[agent_id] = count
+        await self._maybe_snapshot()
+        return count
+
+    async def reset_recovery(self, agent_id: str) -> None:
+        """Clear the nudge budget after real progress (new message or a lifecycle tool)."""
+        async with self._lock:
+            if self.recovery_counts.pop(agent_id, None) is None:
+                return
+        await self._maybe_snapshot()
+
+    async def record_idle_resume(self, agent_id: str) -> int:
+        """Count an auto-resume that no message triggered; return the new total.
+
+        An agent that parks again after every auto-resume would otherwise burn a
+        model turn per timeout for the rest of the scan.
+        """
+        async with self._lock:
+            count = self.idle_resume_counts.get(agent_id, 0) + 1
+            self.idle_resume_counts[agent_id] = count
+        await self._maybe_snapshot()
+        return count
+
+    async def reset_idle_resumes(self, agent_id: str) -> None:
+        async with self._lock:
+            if self.idle_resume_counts.pop(agent_id, None) is None:
+                return
+        await self._maybe_snapshot()
+
     async def set_status(
         self, agent_id: str, status: Status | str, *, error: str | None = None
     ) -> None:
@@ -126,51 +253,55 @@ class AgentCoordinator:
             elif status == "running":
                 self.errors.pop(agent_id, None)
             runtime = self.runtimes.setdefault(agent_id, AgentRuntime())
+            runtime.user_wake_required = status in {"failed", "crashed"}
             runtime.wake.set()
         logger.info("agent.status %s=%s", agent_id, status)
         await self._maybe_snapshot()
 
-    async def send(self, target_agent_id: str, message: dict[str, Any]) -> bool:
-        """Deliver a user/peer message by appending it to the target SDK session."""
+    async def send(
+        self, target_agent_id: str, message: dict[str, Any], *, interrupt: bool = True
+    ) -> bool:
+        """Queue a user/peer message in the target's mailbox and wake it."""
+        from_user = message.get("from") == "user"
+        if from_user and self._budget_paused:
+            await self.resume_from_budget_pause(exclude=target_agent_id)
         async with self._lock:
             if target_agent_id not in self.statuses:
                 logger.debug("agent.send dropped unknown target=%s", target_agent_id)
                 return False
             runtime = self.runtimes.setdefault(target_agent_id, AgentRuntime())
-            session = runtime.session
-            stream = runtime.stream
-            interrupt = runtime.interrupt_on_message
-        if session is None:
-            logger.warning(
-                "agent.send dropped target=%s because its SDK session is not attached",
-                target_agent_id,
-            )
-            return False
-        try:
-            async with session_write_lock(session):
-                await session.add_items([self._message_to_session_item(message)])
-        except Exception:
-            logger.exception(
-                "agent.send failed to append to SDK session target=%s",
-                target_agent_id,
-            )
-            return False
-        async with self._lock:
+            runtime.mailbox.append(dict(message))
             self.pending_counts[target_agent_id] = self.pending_counts.get(target_agent_id, 0) + 1
-            self.runtimes.setdefault(target_agent_id, AgentRuntime()).wake.set()
-        if stream is not None and interrupt:
+            if from_user:
+                runtime.user_wake_required = False
+            runtime.wake.set()
+            stream = runtime.stream
+            interrupt_on_message = runtime.interrupt_on_message
+        if stream is not None and interrupt and interrupt_on_message:
             stream.cancel(mode="immediate")
         await self._maybe_snapshot()
         return True
 
-    async def wait_for_message(self, agent_id: str) -> None:
+    async def wait_for_message(self, agent_id: str, *, timeout: float | None = None) -> bool:
+        """Wait until a message is ready for ``agent_id``; False on ``timeout``."""
         while True:
             async with self._lock:
-                if self._budget_stopped or self.pending_counts.get(agent_id, 0) > 0:
-                    return
-                wake = self.runtimes.setdefault(agent_id, AgentRuntime()).wake
+                runtime = self.runtimes.setdefault(agent_id, AgentRuntime())
+                reserve_exit = self._reserve_stopped and self.parent_of.get(agent_id) is not None
+                pending_ready = (
+                    self.pending_counts.get(agent_id, 0) > 0 and not runtime.user_wake_required
+                )
+                if self._budget_stopped or reserve_exit or pending_ready:
+                    return True
+                wake = runtime.wake
                 wake.clear()
-            await wake.wait()
+            if timeout is None:
+                await wake.wait()
+            else:
+                try:
+                    await asyncio.wait_for(wake.wait(), timeout)
+                except TimeoutError:
+                    return False
 
     async def consume_pending(
         self,
@@ -178,17 +309,38 @@ class AgentCoordinator:
         *,
         include_items: bool = False,
     ) -> tuple[int, list[Any]]:
+        """Drain the agent's mailbox into its own SDK session."""
         async with self._lock:
-            count = self.pending_counts.get(agent_id, 0)
+            runtime = self.runtimes.setdefault(agent_id, AgentRuntime())
+            queued = list(runtime.mailbox)
+            runtime.mailbox.clear()
+            count = max(self.pending_counts.get(agent_id, 0), len(queued))
             self.pending_counts[agent_id] = 0
-            session = self.runtimes.get(agent_id, AgentRuntime()).session
+            session = runtime.session
         if count <= 0:
             return 0, []
+        items = [self._message_to_session_item(m) for m in queued]
+        if items:
+            if session is None:
+                logger.warning(
+                    "agent %s has no SDK session attached; %d queued messages were not persisted",
+                    agent_id,
+                    len(items),
+                )
+            else:
+                try:
+                    async with session_write_lock(session):
+                        await session.add_items(items)
+                except Exception:
+                    logger.exception(
+                        "failed to append %d queued messages to the session of %s",
+                        len(items),
+                        agent_id,
+                    )
         await self._maybe_snapshot()
-        if not include_items or session is None:
+        if not include_items:
             return count, []
-        items = await session.get_items()
-        return count, list(items[-count:])
+        return count, items
 
     async def request_stop(self, agent_id: str) -> None:
         async with self._lock:
@@ -299,7 +451,18 @@ class AgentCoordinator:
                 "names": dict(self.names),
                 "metadata": {aid: dict(md) for aid, md in self.metadata.items()},
                 "pending_counts": dict(self.pending_counts),
+                "recovery_counts": dict(self.recovery_counts),
+                "idle_resume_counts": dict(self.idle_resume_counts),
+                "wait_kinds": dict(self.wait_kinds),
+                "mailboxes": {
+                    aid: [dict(m) for m in runtime.mailbox]
+                    for aid, runtime in self.runtimes.items()
+                    if runtime.mailbox
+                },
                 "errors": dict(self.errors),
+                "budget_stopped": self._budget_stopped,
+                "reserve_stopped": self._reserve_stopped,
+                "budget_paused": self._budget_paused,
             }
 
     async def restore(self, snap: dict[str, Any]) -> None:
@@ -310,6 +473,18 @@ class AgentCoordinator:
             self.metadata = {aid: dict(md) for aid, md in snap.get("metadata", {}).items()}
             self.pending_counts = dict(snap.get("pending_counts", {}))
             self.errors = dict(snap.get("errors", {}))
+            self.recovery_counts = dict(snap.get("recovery_counts", {}))
+            self.idle_resume_counts = dict(snap.get("idle_resume_counts", {}))
+            self.wait_kinds = dict(snap.get("wait_kinds", {}))
+            mailboxes = snap.get("mailboxes", {})
+            if isinstance(mailboxes, dict):
+                for aid, msgs in mailboxes.items():
+                    if isinstance(msgs, list):
+                        runtime = self.runtimes.setdefault(aid, AgentRuntime())
+                        runtime.mailbox = [dict(m) for m in msgs if isinstance(m, dict)]
+            self._budget_stopped = bool(snap.get("budget_stopped", False))
+            self._reserve_stopped = bool(snap.get("reserve_stopped", False))
+            self._budget_paused = bool(snap.get("budget_paused", False))
             for aid in self.statuses:
                 self.runtimes.setdefault(aid, AgentRuntime())
 

strix/core/execution.py

@@ -9,17 +9,29 @@ import uuid
 from collections.abc import Callable
 from typing import TYPE_CHECKING, Any, cast
 
+import litellm
 from agents import RunConfig, Runner
 from agents.exceptions import AgentsException, MaxTurnsExceeded, UserError
 from agents.sandbox.errors import ExecTransportError
 from docker import errors as docker_errors  # type: ignore[import-untyped, unused-ignore]
-from openai import APIError
+from openai import (
+    APIConnectionError,
+    APIError,
+    APITimeoutError,
+)
 
-from strix.core.hooks import BudgetExceededError
+from strix.config import codex
+from strix.core.hooks import (
+    BudgetExceededError,
+    BudgetPausedError,
+    SubagentBudgetReservedError,
+)
 from strix.core.inputs import child_initial_input
 from strix.core.sessions import (
     enforce_image_budget,
     open_agent_session,
+    replace_session_items,
+    seed_initial_input,
     strip_all_images_from_session,
 )
 from strix.llm.compaction import is_context_overflow, maybe_compact
@@ -44,6 +56,23 @@ _INPUT_REJECTION_CODES = frozenset({400, 404, 422})
 _MAX_COMPACTIONS_PER_CYCLE = 2
 
 
+class ProviderRefusalError(AgentsException):
+    """Raised when a provider returns a structured refusal instead of an exception."""
+
+
+def _structured_provider_refusal(result: Any) -> str | None:
+    for item in getattr(result, "new_items", ()) or ():
+        raw_item = getattr(item, "raw_item", None)
+        for content in getattr(raw_item, "content", ()) or ():
+            if getattr(content, "type", None) != "refusal":
+                continue
+            refusal = getattr(content, "refusal", None)
+            if isinstance(refusal, str) and refusal.strip():
+                return refusal.strip()
+            return "The model provider refused this request."
+    return None
+
+
 def _run_config_model(run_config: RunConfig) -> str | None:
     return run_config.model if isinstance(run_config.model, str) else None
 
@@ -78,6 +107,68 @@ async def _compact_session(
     )
 
 
+_MAX_TRANSIENT_MODEL_RETRIES = 5
+_TRANSIENT_MODEL_RETRY_BASE_DELAY_S = 2.0
+_TRANSIENT_MODEL_RETRY_MAX_DELAY_S = 90.0
+
+
+def _model_error_status_code(exc: BaseException) -> int | None:
+    code = getattr(exc, "status_code", None)
+    return code if isinstance(code, int) else None
+
+
+def _is_transient_model_error(exc: BaseException) -> bool:
+    if codex.is_content_guardrail_error(exc):
+        return False
+    if isinstance(
+        exc, APITimeoutError | APIConnectionError | TimeoutError | ConnectionError | OSError
+    ):
+        return True
+    code = _model_error_status_code(exc)
+    if code is not None:
+        return bool(litellm._should_retry(code))
+    return isinstance(exc, APIError)
+
+
+def _transient_model_retry_delay(attempt: int) -> float:
+    delay = _TRANSIENT_MODEL_RETRY_BASE_DELAY_S * float(2 ** (attempt - 1))
+    return min(delay, _TRANSIENT_MODEL_RETRY_MAX_DELAY_S)
+
+
+async def _salvage_stream_to_session(
+    session: Session,
+    pre_run_items: list[Any],
+    stream: Any,
+    agent_id: str,
+) -> None:
+    """Persist a crashed run's full history so a revived agent loses no context."""
+    if stream is None:
+        return
+    try:
+        replay = list(stream.to_input_list())
+    except Exception:
+        logger.exception("could not build salvage history for %s", agent_id)
+        return
+    desired = list(pre_run_items) + replay
+    if len(desired) <= len(pre_run_items):
+        return
+    try:
+        await replace_session_items(session, desired)
+    except Exception:
+        logger.exception("salvaging crashed run history failed for %s", agent_id)
+
+
+async def _seed_and_prepare_first_input(
+    session: Session | None, initial_input: Any, *, start_parked: bool
+) -> Any:
+    """Persist the opening input up front so it survives a first-turn crash."""
+    if initial_input and session is not None and not start_parked:
+        with contextlib.suppress(Exception):
+            if await seed_initial_input(session, initial_input):
+                return []
+    return initial_input
+
+
 async def run_agent_loop(
     *,
     agent: Any,
@@ -100,13 +191,29 @@ async def run_agent_loop(
     )
     result: RunResultBase | None = None
 
+    first_cycle_input = await _seed_and_prepare_first_input(
+        session, initial_input, start_parked=start_parked
+    )
+
+    budget_stopped = coordinator.budget_stopped
+    reserve_stopped = coordinator.reserve_stopped
+    if budget_stopped:
+        await coordinator.set_status(agent_id, "stopped")
+        raise BudgetExceededError("scan budget reached")
+    if reserve_stopped and context.get("parent_id") is not None:
+        await coordinator.set_status(agent_id, "stopped")
+        raise SubagentBudgetReservedError("scan reached the sub-agent budget reserve")
+
+    if reserve_stopped and start_parked and interactive and context.get("parent_id") is None:
+        await coordinator.send(agent_id, _reserve_notice())
+
     if not (start_parked and interactive):
-        if interactive:
-            result = await _run_cycle(
+        with contextlib.suppress(BudgetPausedError):
+            result = await _run_until_lifecycle(
                 agent,
                 coordinator,
                 agent_id,
-                input_data=initial_input,
+                initial_input=first_cycle_input,
                 run_config=run_config,
                 context=context,
                 max_turns=max_turns,
@@ -115,26 +222,14 @@ async def run_agent_loop(
                 event_sink=event_sink,
                 hooks=hooks,
             )
-        else:
-            result = await _run_noninteractive_until_lifecycle(
-                agent,
-                coordinator,
-                agent_id,
-                initial_input=initial_input,
-                run_config=run_config,
-                context=context,
-                max_turns=max_turns,
-                session=session,
-                event_sink=event_sink,
-                hooks=hooks,
-            )
 
     if not interactive:
         return result
 
     while True:
+        timeout = await _plain_waiting_timeout(coordinator, agent_id)
         try:
-            await coordinator.wait_for_message(agent_id)
+            woke = await coordinator.wait_for_message(agent_id, timeout=timeout)
         except asyncio.CancelledError:
             return result
 
@@ -142,20 +237,53 @@ async def run_agent_loop(
             await coordinator.set_status(agent_id, "stopped")
             raise BudgetExceededError("scan budget reached")
 
+        if coordinator.reserve_stopped and context.get("parent_id") is not None:
+            await coordinator.set_status(agent_id, "stopped")
+            raise SubagentBudgetReservedError("scan reached the sub-agent budget reserve")
+
+        if woke:
+            # Real input is real progress, so the nudge budget starts over. A bare
+            # auto-resume is not: it must not hand a wedged agent a fresh budget.
+            await coordinator.reset_recovery(agent_id)
+            await coordinator.reset_idle_resumes(agent_id)
+        else:
+            idle_resumes = await coordinator.record_idle_resume(agent_id)
+            if idle_resumes >= _MAX_IDLE_AUTO_RESUMES:
+                logger.warning(
+                    "agent %s auto-resumed %d times without hearing from anyone; "
+                    "leaving it parked until a real message arrives",
+                    agent_id,
+                    idle_resumes,
+                )
+                await coordinator.park_waiting(agent_id, wait_kind="stalled")
+                await _notify_parent_on_stall(coordinator, agent_id)
+                continue
+            logger.info("agent %s reached its waiting timeout; auto-resuming", agent_id)
+            await coordinator.send(
+                agent_id,
+                {
+                    "from": "system",
+                    "type": "auto_resume",
+                    "content": "Waiting timeout reached. Resuming execution.",
+                },
+                interrupt=False,
+            )
+
         await coordinator.consume_pending(agent_id)
-        result = await _run_cycle(
-            agent,
-            coordinator,
-            agent_id,
-            input_data=[],
-            run_config=run_config,
-            context=context,
-            max_turns=max_turns,
-            session=session,
-            interactive=interactive,
-            event_sink=event_sink,
-            hooks=hooks,
-        )
+        with contextlib.suppress(BudgetPausedError):
+            result = await _run_until_lifecycle(
+                agent,
+                coordinator,
+                agent_id,
+                initial_input=[],
+                run_config=run_config,
+                context=context,
+                max_turns=max_turns,
+                session=session,
+                interactive=True,
+                event_sink=event_sink,
+                hooks=hooks,
+            )
 
 
 async def spawn_child_agent(
@@ -303,7 +431,10 @@ async def respawn_subagents(
                 await coordinator.set_status(child_id, "crashed")
 
 
-async def _run_noninteractive_until_lifecycle(
+_INTERACTIVE_TOOL_RECOVERY_LIMIT = 3
+
+
+async def _run_until_lifecycle(
     agent: Any,
     coordinator: AgentCoordinator,
     agent_id: str,
@@ -313,21 +444,167 @@ async def _run_noninteractive_until_lifecycle(
     context: dict[str, Any],
     max_turns: int,
     session: Session | None,
+    interactive: bool,
     event_sink: StreamEventSink | None,
     hooks: RunHooks[dict[str, Any]] | None,
 ) -> RunResultBase | None:
-    """Non-chat mode keeps running until finish_scan / agent_finish settles status."""
+    """Drive an agent until an explicit lifecycle tool settles its status.
+
+    A turn that ends without ``finish_scan``, ``agent_finish``,
+    ``respond_to_user``, or ``wait_for_agents`` leaves the agent ``running``:
+    plain text never terminates a run and never yields to the user. Such a turn
+    is nudged back into a tool call, bounded by a recovery limit.
+    """
     result: RunResultBase | None = None
     input_data: Any = initial_input
-    invalid_final_outputs = 0
-    invalid_final_output_limit = max(1, max_turns)
+    recovery_limit = _INTERACTIVE_TOOL_RECOVERY_LIMIT if interactive else max(1, max_turns)
 
     while True:
         if coordinator.budget_stopped:
             await coordinator.set_status(agent_id, "stopped")
             raise BudgetExceededError("scan budget reached")
 
-        result = await _run_cycle(
+        if coordinator.reserve_stopped and context.get("parent_id") is not None:
+            await coordinator.set_status(agent_id, "stopped")
+            raise SubagentBudgetReservedError("scan reached the sub-agent budget reserve")
+
+        if interactive:
+            result = await _run_cycle_parked(
+                agent,
+                coordinator,
+                agent_id,
+                input_data=input_data,
+                run_config=run_config,
+                context=context,
+                max_turns=max_turns,
+                session=session,
+                event_sink=event_sink,
+                hooks=hooks,
+            )
+        else:
+            result = await _run_cycle(
+                agent,
+                coordinator,
+                agent_id,
+                input_data=input_data,
+                run_config=run_config,
+                context=context,
+                max_turns=max_turns,
+                session=session,
+                interactive=False,
+                event_sink=event_sink,
+                hooks=hooks,
+            )
+
+        status = await _agent_status(coordinator, agent_id)
+        if status != "running":
+            await coordinator.reset_recovery(agent_id)
+            return result
+
+        recoveries = await coordinator.record_recovery(agent_id)
+        logger.warning(
+            "agent %s ended a turn without a lifecycle tool call (interactive=%s); "
+            "forcing tool continuation (%d/%d): %s",
+            agent_id,
+            interactive,
+            recoveries,
+            recovery_limit,
+            _final_output_preview(result),
+        )
+
+        if recoveries >= recovery_limit:
+            return await _exhausted_recovery(coordinator, agent_id, result, interactive=interactive)
+
+        input_data = await _append_tool_required_message(
+            session=session,
+            context=context,
+            attempt=recoveries,
+            limit=recovery_limit,
+            interactive=interactive,
+        )
+
+
+async def _exhausted_recovery(
+    coordinator: AgentCoordinator,
+    agent_id: str,
+    result: RunResultBase | None,
+    *,
+    interactive: bool,
+) -> RunResultBase | None:
+    """Settle an agent that never recovered into a tool call.
+
+    Interactive runs park instead of dying: a human is attached and can message
+    any agent, so the scan stays resumable. Autonomous runs have nobody to
+    resume them, so they fail loudly.
+    """
+    if not interactive:
+        await coordinator.set_status(agent_id, "crashed")
+        await _notify_parent_on_terminal(coordinator, agent_id, "crashed")
+        raise MaxTurnsExceeded(
+            "Agent exhausted recovery attempts without calling finish_scan or agent_finish."
+        )
+
+    logger.warning(
+        "agent %s exhausted tool-call recovery attempts; parking until a message arrives",
+        agent_id,
+    )
+    await coordinator.park_waiting(agent_id, wait_kind="stalled")
+    # A parked child owes its parent a completion report it can no longer send. The
+    # parent is an agent, not a watching human, so nothing else tells it to stop
+    # waiting and it burns its full timeout on a message that is never coming.
+    await _notify_parent_on_stall(coordinator, agent_id)
+    return result
+
+
+_WAITING_AUTO_RESUME_TIMEOUT_S = 300.0
+
+# An agent that parks again after every auto-resume makes no progress, so stop
+# spending a model turn per timeout and leave it parked for a real message.
+_MAX_IDLE_AUTO_RESUMES = 3
+
+
+async def _plain_waiting_timeout(
+    coordinator: AgentCoordinator,
+    agent_id: str,
+) -> float | None:
+    """Auto-resume timeout for a parked agent; None waits until a message arrives.
+
+    Driven by what the agent is waiting on, not by where it sits in the graph:
+    the user can message any agent, so an agent awaiting a human parks
+    indefinitely whether or not it is the root. Only an agent awaiting other
+    agents is re-checked on a timer, and only until it has spent its idle
+    budget re-parking without hearing anything.
+    """
+    async with coordinator._lock:
+        status = coordinator.statuses.get(agent_id)
+        has_error = agent_id in coordinator.errors
+        runtime = coordinator.runtimes.get(agent_id)
+        gated = runtime.user_wake_required if runtime is not None else False
+        wait_kind = coordinator.wait_kinds.get(agent_id)
+        idle_resumes = coordinator.idle_resume_counts.get(agent_id, 0)
+    if status != "waiting" or has_error or gated:
+        return None
+    if wait_kind != "agents" or idle_resumes >= _MAX_IDLE_AUTO_RESUMES:
+        return None
+    return _WAITING_AUTO_RESUME_TIMEOUT_S
+
+
+async def _run_cycle_parked(
+    agent: Any,
+    coordinator: AgentCoordinator,
+    agent_id: str,
+    *,
+    input_data: Any,
+    run_config: RunConfig,
+    context: dict[str, Any],
+    max_turns: int,
+    session: Session | None,
+    event_sink: StreamEventSink | None,
+    hooks: RunHooks[dict[str, Any]] | None,
+) -> RunResultBase | None:
+    """Interactive run cycle that parks on any error instead of killing the runner."""
+    try:
+        return await _run_cycle(
             agent,
             coordinator,
             agent_id,
@@ -336,39 +613,17 @@ async def _run_noninteractive_until_lifecycle(
             context=context,
             max_turns=max_turns,
             session=session,
-            interactive=False,
+            interactive=True,
             event_sink=event_sink,
             hooks=hooks,
         )
-
-        status = await _agent_status(coordinator, agent_id)
-        if status != "running":
-            return result
-
-        invalid_final_outputs += 1
-        logger.warning(
-            "agent %s produced non-lifecycle final output in non-interactive mode; "
-            "forcing tool continuation (%d/%d): %s",
-            agent_id,
-            invalid_final_outputs,
-            invalid_final_output_limit,
-            _final_output_preview(result),
-        )
-
-        if invalid_final_outputs >= invalid_final_output_limit:
-            await coordinator.set_status(agent_id, "crashed")
-            await _notify_parent_on_crash(coordinator, agent_id, "crashed")
-            raise MaxTurnsExceeded(
-                "Agent exhausted non-interactive recovery attempts without calling "
-                "finish_scan or agent_finish."
-            )
-
-        input_data = await _append_noninteractive_tool_required_message(
-            session=session,
-            context=context,
-            attempt=invalid_final_outputs,
-            limit=invalid_final_output_limit,
-        )
+    except (BudgetExceededError, BudgetPausedError, SubagentBudgetReservedError):
+        raise
+    except Exception as exc:
+        logger.exception("error escaped the run cycle for %s; parking as failed", agent_id)
+        await coordinator.set_status(agent_id, "failed", error=str(exc) or type(exc).__name__)
+        await _notify_parent_on_terminal(coordinator, agent_id, "failed")
+        return None
 
 
 async def _run_cycle(  # noqa: PLR0912, PLR0915
@@ -387,7 +642,10 @@ async def _run_cycle(  # noqa: PLR0912, PLR0915
 ) -> RunResultBase | None:
     image_strips = 0
     compactions = 0
+    model_retries = 0
     while True:
+        stream: Any = None
+        pre_run_items: list[Any] = []
         try:
             await coordinator.mark_running(agent_id)
             if session is not None:
@@ -401,6 +659,8 @@ async def _run_cycle(  # noqa: PLR0912, PLR0915
                     await _compact_session(agent, session, run_config, force=False)
                 except Exception:
                     logger.exception("proactive compaction failed for %s", agent_id)
+                with contextlib.suppress(Exception):
+                    pre_run_items = list(await session.get_items())
             stream = Runner.run_streamed(
                 agent,
                 input=input_data,
@@ -421,9 +681,9 @@ async def _run_cycle(  # noqa: PLR0912, PLR0915
                                 logger.exception("stream event sink failed for %s", agent_id)
                     if stream.run_loop_exception is not None:
                         raise stream.run_loop_exception
-                except BudgetExceededError:
-                    # A RuntimeError subclass: re-raise explicitly so it is never
-                    # mistaken for the LiteLLM "after shutdown" race below.
+                    if refusal := _structured_provider_refusal(stream):
+                        raise ProviderRefusalError(refusal)
+                except (BudgetExceededError, BudgetPausedError, SubagentBudgetReservedError):
                     raise
                 except RuntimeError as stream_exc:
                     if "after shutdown" not in str(stream_exc):
@@ -442,6 +702,15 @@ async def _run_cycle(  # noqa: PLR0912, PLR0915
                     )
             finally:
                 await coordinator.detach_stream(agent_id, stream)
+        except BudgetPausedError as exc:
+            logger.info("agent %s paused at the scan budget limit: %s", agent_id, exc)
+            await coordinator.pause_for_budget(agent_id)
+            raise
+        except SubagentBudgetReservedError as exc:
+            logger.info("sub-agent %s stopped at the budget reserve: %s", agent_id, exc)
+            await coordinator.set_status(agent_id, "stopped")
+            await _notify_root_on_budget_reserve(coordinator)
+            raise
         except BudgetExceededError as exc:
             logger.info(
                 "agent %s reached the scan budget limit; stopping the scan: %s", agent_id, exc
@@ -488,6 +757,29 @@ async def _run_cycle(  # noqa: PLR0912, PLR0915
                     )
                     input_data = []
                     continue
+            if model_retries < _MAX_TRANSIENT_MODEL_RETRIES and _is_transient_model_error(exc):
+                model_retries += 1
+                delay = _transient_model_retry_delay(model_retries)
+                logger.warning(
+                    "transient model/provider error for %s; replaying turn "
+                    "(attempt %d/%d, backoff %.1fs): %r",
+                    agent_id,
+                    model_retries,
+                    _MAX_TRANSIENT_MODEL_RETRIES,
+                    delay,
+                    exc,
+                )
+                await asyncio.sleep(delay)
+                if session is not None:
+                    input_data = []
+                continue
+            if session is not None:
+                await _salvage_stream_to_session(session, pre_run_items, stream, agent_id)
+            if isinstance(exc, ProviderRefusalError):
+                logger.warning("agent %s refused by the model provider: %s", agent_id, exc)
+                await coordinator.set_status(agent_id, "failed", error=str(exc))
+                await _notify_parent_on_terminal(coordinator, agent_id, "failed")
+                return None
             if not interactive:
                 raise
             if isinstance(exc, MaxTurnsExceeded):
@@ -498,28 +790,10 @@ async def _run_cycle(  # noqa: PLR0912, PLR0915
                 status = "crashed"
             logger.exception("agent run failed for %s; parking as %s", agent_id, status)
             await coordinator.set_status(agent_id, status, error=str(exc) or type(exc).__name__)
-            await _notify_parent_on_crash(coordinator, agent_id, status)
+            await _notify_parent_on_terminal(coordinator, agent_id, status)
             return None
         else:
-            await _settle_run_result(coordinator, agent_id, interactive)
-            return stream
-
-
-async def _settle_run_result(
-    coordinator: AgentCoordinator,
-    agent_id: str,
-    interactive: bool,
-) -> None:
-    async with coordinator._lock:
-        current_status = coordinator.statuses.get(agent_id)
-
-    if current_status != "running":
-        return
-
-    if not interactive:
-        return
-
-    await coordinator.set_status(agent_id, "waiting")
+            return cast("RunResultBase | None", stream)
 
 
 async def _agent_status(coordinator: AgentCoordinator, agent_id: str) -> Status | None:
@@ -537,23 +811,37 @@ def _final_output_preview(result: RunResultBase | None) -> str:
     return text[:300]
 
 
-async def _append_noninteractive_tool_required_message(
+async def _append_tool_required_message(
     *,
     session: Session | None,
     context: dict[str, Any],
     attempt: int,
     limit: int,
+    interactive: bool,
 ) -> list[dict[str, str]]:
     finish_tool = "finish_scan" if context.get("parent_id") is None else "agent_finish"
-    message = (
-        "Your previous response ended the autonomous Strix run without a lifecycle tool call. "
-        "That is invalid in non-interactive mode; plain text final answers are ignored. "
-        "Continue immediately and call exactly one tool. "
-        f"If your work is complete, call {finish_tool}. "
-        "If you are blocked waiting for another agent, call wait_for_message. "
-        "Otherwise use the appropriate execution or planning tool. "
-        f"This is recovery attempt {attempt}/{limit}."
-    )
+    if interactive:
+        message = (
+            "Your previous message ended a turn without a tool call. Plain text never ends "
+            "execution and never hands control to the user: it is shown to the user, and the "
+            "run continues. Continue immediately and call exactly one tool. "
+            "If you have something to tell the user and nothing to do until they reply, "
+            "call respond_to_user. "
+            "If you are blocked waiting for another agent, call wait_for_agents. "
+            f"If the whole engagement is complete, call {finish_tool}. "
+            "Otherwise use the appropriate execution or planning tool. "
+            f"This is recovery attempt {attempt}/{limit}."
+        )
+    else:
+        message = (
+            "Your previous response ended the autonomous Strix run without a lifecycle tool "
+            "call. That is invalid in non-interactive mode; plain text final answers are "
+            "ignored. Continue immediately and call exactly one tool. "
+            f"If your work is complete, call {finish_tool}. "
+            "If you are blocked waiting for another agent, call wait_for_agents. "
+            "Otherwise use the appropriate execution or planning tool. "
+            f"This is recovery attempt {attempt}/{limit}."
+        )
     item = {"role": "user", "content": message}
     if session is None:
         return [item]
@@ -562,12 +850,61 @@ async def _append_noninteractive_tool_required_message(
     return []
 
 
-async def _notify_parent_on_crash(
+_TERMINAL_NOTICE = {
+    "crashed": (
+        "[Agent crash] {name} ({agent_id}) terminated unexpectedly. "
+        "Stop waiting on this child unless you want to message it again."
+    ),
+    "failed": (
+        "[Agent failed] {name} ({agent_id}) stopped with an error and will not "
+        "send a completion report. Stop waiting on this child unless you want to "
+        "message it again."
+    ),
+    "stopped": (
+        "[Agent capped] {name} ({agent_id}) hit its turn limit and was stopped "
+        "before finishing. It will not send a completion report, so stop waiting "
+        "on this child; account for its capped subtask and continue."
+    ),
+}
+
+
+_STALL_NOTICE = (
+    "[Agent stalled] {name} ({agent_id}) kept ending turns without a tool call and is "
+    "parked until it receives a message. It will not send a completion report on its "
+    "own: either message it with a concrete next step to unblock it, or stop waiting on "
+    "it and account for its unfinished subtask."
+)
+
+
+async def _notify_parent_on_stall(
+    coordinator: AgentCoordinator,
+    agent_id: str,
+) -> None:
+    """Tell the parent that a child parked mid-task, so it stops waiting blindly."""
+    async with coordinator._lock:
+        parent = coordinator.parent_of.get(agent_id)
+        name = coordinator.names.get(agent_id, agent_id)
+    if parent is None:
+        return
+    await coordinator.send(
+        parent,
+        {
+            "from": agent_id,
+            "type": "stalled",
+            "priority": "high",
+            "content": _STALL_NOTICE.format(name=name, agent_id=agent_id),
+        },
+        interrupt=False,
+    )
+
+
+async def _notify_parent_on_terminal(
     coordinator: AgentCoordinator,
     agent_id: str,
     status: str,
 ) -> None:
-    if status != "crashed":
+    template = _TERMINAL_NOTICE.get(status)
+    if template is None:
         return
     async with coordinator._lock:
         parent = coordinator.parent_of.get(agent_id)
@@ -578,16 +915,36 @@ async def _notify_parent_on_crash(
         parent,
         {
             "from": agent_id,
-            "type": "crash",
+            "type": status,
             "priority": "high",
-            "content": (
-                f"[Agent crash] {name} ({agent_id}) terminated unexpectedly. "
-                "Stop waiting on this child unless you want to message it again."
-            ),
+            "content": template.format(name=name, agent_id=agent_id),
         },
+        interrupt=False,
     )
 
 
+def _reserve_notice() -> dict[str, Any]:
+    return {
+        "from": "system",
+        "type": "budget_reserve_stop",
+        "priority": "high",
+        "content": (
+            "[Budget reserve] The scan has reached the sub-agent budget reserve: every "
+            "sub-agent is being force-stopped as soon as its in-flight turn completes, and "
+            "none will send a completion report. Their confirmed vulnerabilities are "
+            "already filed as they were found. Do not wait on any sub-agents and do not "
+            "spawn new ones — wrap up now and call finish_scan."
+        ),
+    }
+
+
+async def _notify_root_on_budget_reserve(coordinator: AgentCoordinator) -> None:
+    root = await coordinator.claim_reserve_notification()
+    if root is None:
+        return
+    await coordinator.send(root, _reserve_notice())
+
+
 async def _start_child_runner(
     *,
     parent_ctx: dict[str, Any],
@@ -639,6 +996,8 @@ async def _start_child_runner(
             )
         except BudgetExceededError:
             logger.info("child %s stopped after reaching the scan budget limit", child_id)
+        except SubagentBudgetReservedError:
+            logger.info("child %s stopped at the sub-agent budget reserve", child_id)
 
     task_handle = asyncio.create_task(_child_loop(), name=f"agent-{name}-{child_id}")
     await coordinator.attach_runtime(child_id, task=task_handle)

strix/core/hooks.py

@@ -14,26 +14,210 @@ from strix.report.state import get_global_report_state
 if TYPE_CHECKING:
     from agents import RunContextWrapper
     from agents.agent import Agent
-    from agents.items import ModelResponse
+    from agents.items import ModelResponse, TResponseInputItem
 
 
 logger = logging.getLogger(__name__)
 
 
+_STAGE_LABELS: tuple[str, ...] = ("NOTICE", "URGENT", "CRITICAL")
+_TURN_WARN_BANDS: tuple[float, ...] = (0.70, 0.85, 0.95)
+_ROOT_BUDGET_WARN_BANDS: tuple[float, ...] = (0.70, 0.85, 0.95)
+_SUBAGENT_BUDGET_WARN_BANDS: tuple[float, ...] = (0.75, 0.80, 0.85)
+_SUBAGENT_BUDGET_RESERVE = 0.90
+
+
 class BudgetExceededError(RuntimeError):
     """Raised when the accumulated LLM cost reaches the configured budget."""
 
 
-class ReportUsageHooks(RunHooks[dict[str, Any]]):
-    """Persist SDK-native usage after every model response."""
+class SubagentBudgetReservedError(RuntimeError):
+    """Raised to stop a single sub-agent once the reserve threshold is crossed."""
 
-    def __init__(self, *, model: str, max_budget_usd: float | None = None) -> None:
+
+class BudgetPausedError(RuntimeError):
+    """Raised to park one agent when an interactive scan reaches its budget."""
+
+
+def recomputed_budget_flags(
+    cost: float,
+    max_budget_usd: float | None,
+    *,
+    interactive: bool,
+) -> tuple[bool, bool]:
+    """Return the (budget_stopped, reserve_stopped) flags a resumed scan should carry."""
+    if max_budget_usd is None:
+        return False, False
+    if interactive:
+        return False, False
+    budget_stopped = cost >= max_budget_usd
+    reserve_stopped = cost >= max_budget_usd * _SUBAGENT_BUDGET_RESERVE
+    return budget_stopped, reserve_stopped
+
+
+def _crossed_stage(fraction: float, bands: tuple[float, ...]) -> int | None:
+    crossed: int | None = None
+    for index, band in enumerate(bands):
+        if fraction >= band:
+            crossed = index
+    return crossed
+
+
+_ROOT_DIRECTIVES: tuple[str, ...] = (
+    (
+        "As the root agent, begin planning your wind-down of the whole scan: avoid "
+        "starting large new lines of investigation, and keep your required objectives on "
+        "track so you can call finish_scan comfortably before the limit."
+    ),
+    (
+        "As the root agent, prioritize wrapping up the whole scan now: stop opening new "
+        "lines of investigation, close out only what is essential, and move toward calling "
+        "finish_scan to compile and deliver the final report."
+    ),
+    (
+        "As the root agent, STOP all other work on the whole scan and finish immediately: "
+        "secure your findings and call finish_scan now — anything left unfinished when the "
+        "limit is hit is discarded."
+    ),
+)
+_SUBAGENT_DIRECTIVES: tuple[str, ...] = (
+    (
+        "As a sub-agent, begin planning your wind-down: avoid starting large new subtasks, "
+        "and if you are close to a confirmed, validated vulnerability, drive it to a result "
+        "you can report."
+    ),
+    (
+        "As a sub-agent, prioritize wrapping up your task now: report any confirmed, "
+        "validated vulnerability, finish work that is nearly done rather than starting "
+        "anything new, and prepare to call agent_finish."
+    ),
+    (
+        "As a sub-agent, STOP all other work and finish immediately: report any confirmed "
+        "vulnerability right now and call agent_finish to hand your results back to your "
+        "parent before you are cut off."
+    ),
+)
+
+
+def _wrapup_directive(context: RunContextWrapper[dict[str, Any]], stage: int) -> str:
+    is_root = context.context.get("parent_id") is None
+    directives = _ROOT_DIRECTIVES if is_root else _SUBAGENT_DIRECTIVES
+    return directives[stage]
+
+
+def _urgency(stage: int) -> str:
+    return _STAGE_LABELS[stage]
+
+
+class ReportUsageHooks(RunHooks[dict[str, Any]]):
+    """Persist SDK-native usage and warn/stop as turn and cost budgets are consumed."""
+
+    def __init__(
+        self,
+        *,
+        model: str,
+        max_budget_usd: float | None = None,
+        max_turns: int | None = None,
+        interactive: bool = False,
+    ) -> None:
         if max_budget_usd is not None and (
             not math.isfinite(max_budget_usd) or max_budget_usd <= 0
         ):
             raise ValueError("max_budget_usd must be a finite number greater than 0")
+        if max_turns is not None and max_turns <= 0:
+            raise ValueError("max_turns must be a positive integer")
         self._model = model
         self._max_budget_usd = max_budget_usd
+        self._budget_increment = max_budget_usd
+        self._max_turns = max_turns
+        self._interactive = interactive
+
+    def extend_budget(self) -> None:
+        if self._max_budget_usd is None or self._budget_increment is None:
+            return
+        self._max_budget_usd += self._budget_increment
+
+    async def on_llm_start(
+        self,
+        context: RunContextWrapper[dict[str, Any]],
+        agent: Agent[dict[str, Any]],  # noqa: ARG002
+        system_prompt: str | None,  # noqa: ARG002
+        input_items: list[TResponseInputItem],
+    ) -> None:
+        try:
+            self._maybe_warn_turns(context, input_items)
+            self._maybe_warn_budget(context, input_items)
+        except Exception:
+            logger.exception("budget/turn warning injection failed")
+
+    def _maybe_warn_turns(
+        self,
+        context: RunContextWrapper[dict[str, Any]],
+        input_items: list[TResponseInputItem],
+    ) -> None:
+        if not self._max_turns:
+            return
+        usage = getattr(context, "usage", None)
+        requests = getattr(usage, "requests", None)
+        if not isinstance(requests, int):
+            return
+        turns_used = requests + 1
+        stage = _crossed_stage(turns_used / self._max_turns, _TURN_WARN_BANDS)
+        if stage is None:
+            return
+        remaining = max(self._max_turns - turns_used, 0)
+        pct = round(100 * turns_used / self._max_turns)
+        content = (
+            f"[{_urgency(stage)}] Turn budget: {turns_used}/{self._max_turns} used ({pct}%). "
+            f"About {remaining} turn(s) remain before this agent is force-stopped and any "
+            f"in-progress work is discarded. {_wrapup_directive(context, stage)}"
+        )
+        input_items.append({"role": "user", "content": content})
+
+    def _maybe_warn_budget(
+        self,
+        context: RunContextWrapper[dict[str, Any]],
+        input_items: list[TResponseInputItem],
+    ) -> None:
+        if self._max_budget_usd is None:
+            return
+        report_state = get_global_report_state()
+        if report_state is None:
+            return
+        cost = report_state.get_total_llm_cost()
+        is_root = context.context.get("parent_id") is None
+        if self._interactive:
+            bands = _ROOT_BUDGET_WARN_BANDS
+        else:
+            bands = _ROOT_BUDGET_WARN_BANDS if is_root else _SUBAGENT_BUDGET_WARN_BANDS
+        stage = _crossed_stage(cost / self._max_budget_usd, bands)
+        if stage is None:
+            return
+        pct = round(100 * cost / self._max_budget_usd)
+        reserve_pct = round(_SUBAGENT_BUDGET_RESERVE * 100)
+        if self._interactive:
+            content = (
+                f"[{_urgency(stage)}] Scan cost budget: ${cost:.2f}/${self._max_budget_usd:.2f} "
+                f"spent ({pct}%). This budget is shared across every agent in the scan; when it "
+                "is reached all agents are paused until the user chooses to continue. "
+                f"{_wrapup_directive(context, stage)}"
+            )
+        elif is_root:
+            content = (
+                f"[{_urgency(stage)}] Scan cost budget: ${cost:.2f}/${self._max_budget_usd:.2f} "
+                f"spent ({pct}%). This budget is shared across every agent in the scan; when it "
+                "is reached the whole scan is stopped immediately, and sub-agents are stopped at "
+                f"{reserve_pct}% to reserve the remainder for your final report. "
+                f"{_wrapup_directive(context, stage)}"
+            )
+        else:
+            content = (
+                f"[{_urgency(stage)}] Scan cost budget: ${cost:.2f}/${self._max_budget_usd:.2f} "
+                f"spent ({pct}%). This budget is shared across every agent in the scan; "
+                f"sub-agents are stopped at {reserve_pct}% to leave the remainder for the root "
+                f"agent's final report. {_wrapup_directive(context, stage)}"
+            )
+        input_items.append({"role": "user", "content": content})
 
     async def on_llm_end(
         self,
@@ -66,6 +250,21 @@ class ReportUsageHooks(RunHooks[dict[str, Any]]):
         if self._max_budget_usd is not None:
             cost = report_state.get_total_llm_cost()
             if cost >= self._max_budget_usd:
+                if self._interactive:
+                    raise BudgetPausedError(
+                        f"Scan budget of ${self._max_budget_usd:.2f} reached "
+                        f"(spent ${cost:.4f}); pausing until the user continues"
+                    )
                 raise BudgetExceededError(
                     f"Token budget of ${self._max_budget_usd:.2f} exceeded (spent ${cost:.4f})"
                 )
+            is_root = ctx.get("parent_id") is None
+            if not self._interactive and not is_root:
+                reserve_limit = self._max_budget_usd * _SUBAGENT_BUDGET_RESERVE
+                if cost >= reserve_limit:
+                    raise SubagentBudgetReservedError(
+                        f"Sub-agent budget reserve reached: spent ${cost:.4f} of "
+                        f"${self._max_budget_usd:.2f} "
+                        f"(>= {round(_SUBAGENT_BUDGET_RESERVE * 100)}% reserve); stopping this "
+                        "sub-agent so the root agent can finish the scan."
+                    )

strix/core/inputs.py

@@ -10,6 +10,9 @@ from openai.types.shared import Reasoning
 
 from strix.config.models import (
     DEFAULT_MODEL_RETRY,
+    bedrock_route_supports_prompt_caching,
+    is_bedrock_route,
+    is_claude_model,
     is_known_openai_bare_model,
     model_supports_reasoning,
     request_timeout_extra_args,
@@ -128,12 +131,15 @@ def make_model_settings(
     model_name: str,
     force_required_tool_choice: bool = False,
     request_timeout: float | None = None,
+    prompt_cache: bool = True,
+    extra_headers: dict[str, str] | None = None,
 ) -> ModelSettings:
     model_settings = ModelSettings(
         parallel_tool_calls=False,
         retry=DEFAULT_MODEL_RETRY,
         include_usage=True,
         extra_args=request_timeout_extra_args(request_timeout),
+        extra_headers=dict(extra_headers) if extra_headers else None,
     )
     if (
         reasoning_effort is not None
@@ -145,9 +151,38 @@ def make_model_settings(
         )
     if force_required_tool_choice and _accepts_required_tool_choice(model_name):
         model_settings = model_settings.resolve(ModelSettings(tool_choice="required"))
+
+    cache_extra_args = _prompt_cache_extra_args(model_name) if prompt_cache else None
+    if cache_extra_args:
+        model_settings = model_settings.resolve(
+            ModelSettings(
+                extra_args={**(model_settings.extra_args or {}), **cache_extra_args},
+            ),
+        )
     return model_settings
 
 
+def _prompt_cache_extra_args(model_name: str) -> dict[str, Any] | None:
+    """LiteLLM ``cache_control_injection_points`` for Claude prompt caching.
+
+    System prompt + rolling last-message breakpoint everywhere; ``tool_config``
+    only on Bedrock Converse (the only route whose LiteLLM transform consumes
+    it — elsewhere it leaks onto the wire and native Anthropic 400s). Unmapped
+    Bedrock models get no points at all: Bedrock rejects the passed-through
+    field outright.
+    """
+    if not is_claude_model(model_name):
+        return None
+    if is_bedrock_route(model_name) and not bedrock_route_supports_prompt_caching(model_name):
+        return None
+
+    points: list[dict[str, Any]] = [{"location": "message", "role": "system"}]
+    if is_bedrock_route(model_name):
+        points.append({"location": "tool_config"})
+    points.append({"location": "message", "index": -1})
+    return {"cache_control_injection_points": points}
+
+
 def child_initial_input(
     *,
     name: str,

strix/core/runner.py

@@ -31,7 +31,7 @@ from strix.core.execution import (
 from strix.core.execution import (
     spawn_child_agent as start_child_agent,
 )
-from strix.core.hooks import BudgetExceededError, ReportUsageHooks
+from strix.core.hooks import BudgetExceededError, ReportUsageHooks, recomputed_budget_flags
 from strix.core.inputs import (
     DEFAULT_MAX_TURNS,
     build_root_task,
@@ -40,6 +40,7 @@ from strix.core.inputs import (
 )
 from strix.core.paths import run_dir_for, runtime_state_dir
 from strix.core.sessions import open_agent_session
+from strix.report.state import get_global_report_state
 from strix.runtime import session_manager
 from strix.telemetry.logging import set_scan_id, setup_scan_logging
 from strix.tools.output_store import (
@@ -185,6 +186,18 @@ async def run_strix_scan(
                 f"Cannot resume scan {scan_id}: missing SDK session database at {agents_db}",
             )
         await coordinator.restore(snap)
+        report_state = get_global_report_state()
+        if report_state is not None:
+            budget_stopped, reserve_stopped = recomputed_budget_flags(
+                report_state.get_total_llm_cost(),
+                max_budget_usd,
+                interactive=interactive,
+            )
+            await coordinator.reset_budget_stops(
+                budget_stopped=budget_stopped,
+                reserve_stopped=reserve_stopped,
+                budget_paused=interactive and coordinator.budget_paused,
+            )
         for aid, parent in coordinator.parent_of.items():
             if parent is None:
                 root_id = aid
@@ -236,6 +249,8 @@ async def run_strix_scan(
             model_name=resolved_model,
             force_required_tool_choice=settings.llm.force_required_tool_choice,
             request_timeout=settings.llm.timeout,
+            prompt_cache=settings.llm.prompt_cache,
+            extra_headers=settings.llm.extra_headers,
         )
         run_config = RunConfig(
             model=resolved_model,
@@ -244,7 +259,14 @@ async def run_strix_scan(
             sandbox=SandboxRunConfig(client=bundle["client"], session=bundle["session"]),
             trace_include_sensitive_data=False,
         )
-        hooks = ReportUsageHooks(model=resolved_model, max_budget_usd=max_budget_usd)
+        hooks = ReportUsageHooks(
+            model=resolved_model,
+            max_budget_usd=max_budget_usd,
+            max_turns=max_turns,
+            interactive=interactive,
+        )
+        if interactive:
+            coordinator.set_budget_extender(hooks.extend_budget)
 
         scope_context = build_scope_context(scan_config)
         root_context = _merge_root_prompt_context(scope_context, extra_system_prompt_context)

strix/core/sessions.py

@@ -7,6 +7,7 @@ import logging
 from typing import TYPE_CHECKING, Any, cast
 from weakref import WeakKeyDictionary
 
+from agents.items import ItemHelpers
 from agents.memory import SQLiteSession
 
 
@@ -26,6 +27,18 @@ def open_agent_session(agent_id: str, path: Path) -> SQLiteSession:
     return SQLiteSession(session_id=agent_id, db_path=path)
 
 
+async def seed_initial_input(session: Session, initial_input: Any) -> bool:
+    """Commit an agent's opening identity/task input before its first run cycle."""
+    items = ItemHelpers.input_to_new_input_list(initial_input)
+    if not items:
+        return False
+    async with session_write_lock(session):
+        if await session.get_items():
+            return False
+        await session.add_items(items)
+    return True
+
+
 _IMAGE_REJECTED_TEXT = "[image rejected by the model]"
 _IMAGE_ELIDED_TEXT = "[older screenshot elided to bound context memory]"
 _INHERITED_IMAGE_TEXT = "[screenshot omitted from inherited context]"

strix/interface/cli.py

@@ -13,6 +13,7 @@ from rich.panel import Panel
 from rich.text import Text
 
 from strix.config import load_settings
+from strix.core.inputs import DEFAULT_MAX_TURNS
 from strix.core.runner import run_strix_scan
 from strix.report.state import ReportState, set_global_report_state
 from strix.runtime import session_manager
@@ -184,6 +185,7 @@ async def run_cli(args: Any) -> None:  # noqa: PLR0915
                     local_sources=getattr(args, "local_sources", None) or [],
                     interactive=bool(getattr(args, "interactive", False)),
                     max_budget_usd=getattr(args, "max_budget_usd", None),
+                    max_turns=getattr(args, "max_turns", DEFAULT_MAX_TURNS),
                 )
             finally:
                 stop_updates.set()

strix/interface/main.py

@@ -31,6 +31,7 @@ from strix.config.models import (
     is_known_openai_bare_model,
     is_recommended_or_frontier_model,
 )
+from strix.core.inputs import DEFAULT_MAX_TURNS, make_model_settings
 from strix.core.paths import run_dir_for, runtime_state_dir
 from strix.interface.cli import run_cli
 from strix.interface.tui import run_tui
@@ -210,7 +211,7 @@ def validate_environment() -> None:
             padding=(1, 2),
         )
 
-        logger.error("Missing required env vars: %s", missing_required_vars)
+        logger.debug("Missing required env vars: %s", missing_required_vars)
         console.print("\n")
         console.print(panel)
         console.print()
@@ -223,7 +224,7 @@ def validate_environment() -> None:
 
 def check_docker_installed() -> None:
     if shutil.which("docker") is None:
-        logger.error("Docker CLI not found in PATH")
+        logger.debug("Docker CLI not found in PATH")
         console = Console()
         error_text = Text()
         error_text.append("DOCKER NOT INSTALLED", style="bold red")
@@ -381,7 +382,13 @@ async def warm_up_llm(show_model_warning: bool = True) -> None:
             model.get_response(
                 system_instructions="You are a helpful assistant.",
                 input="Reply with just 'OK'.",
-                model_settings=ModelSettings(),
+                model_settings=make_model_settings(
+                    None,
+                    model_name=raw_model,
+                    request_timeout=llm.timeout,
+                    prompt_cache=False,
+                    extra_headers=llm.extra_headers,
+                ),
                 tools=[],
                 output_schema=None,
                 handoffs=[],
@@ -403,7 +410,19 @@ async def warm_up_llm(show_model_warning: bool = True) -> None:
             # Match the runtime path: send the dedupe key/endpoint per call so a
             # separate-provider dedupe model authenticates during warm-up too.
             deduper_extra = _dedupe_extra_args(settings.dedupe)
-            deduper_settings = ModelSettings(extra_args=deduper_extra or None)
+            # A dedicated dedupe model may route to another provider, which must
+            # never receive the main endpoint's headers; it has its own
+            # DEDUPE_LLM_EXTRA_HEADERS.
+            deduper_settings = make_model_settings(
+                None,
+                model_name=dedupe_model,
+                request_timeout=llm.timeout,
+                prompt_cache=False,
+                extra_headers=settings.dedupe.extra_headers,
+            )
+            if deduper_extra:
+                merged = {**(deduper_settings.extra_args or {}), **deduper_extra}
+                deduper_settings = deduper_settings.resolve(ModelSettings(extra_args=merged))
             await asyncio.wait_for(
                 deduper.get_response(
                     system_instructions="You are a helpful assistant.",
@@ -422,7 +441,7 @@ async def warm_up_llm(show_model_warning: bool = True) -> None:
             logger.info("LLM warm-up succeeded for dedupe model %s", dedupe_model)
 
     except Exception as e:
-        logger.exception("LLM warm-up failed")
+        logger.debug("LLM warm-up failed", exc_info=True)
         error_text = Text()
         sub_hint = _subscription_error_hint(e)
         if sub_hint is not None:
@@ -481,6 +500,16 @@ def _positive_budget(value: str) -> float:
     return budget
 
 
+def _positive_int(value: str) -> int:
+    try:
+        parsed = int(value)
+    except ValueError as exc:
+        raise argparse.ArgumentTypeError(f"invalid int value: {value!r}") from exc
+    if parsed <= 0:
+        raise argparse.ArgumentTypeError("must be an integer greater than 0")
+    return parsed
+
+
 def parse_arguments() -> argparse.Namespace:
     parser = argparse.ArgumentParser(
         description="Strix Multi-Agent Cybersecurity Penetration Testing Tool",
@@ -636,10 +665,27 @@ Examples:
     )
 
     parser.add_argument(
-        "--max-budget-usd",
+        "--max-budget",
+        dest="max_budget_usd",
+        metavar="USD",
         type=_positive_budget,
         default=None,
-        help="Maximum LLM cost in USD (> 0). The scan stops cleanly when this limit is reached.",
+        help=(
+            "Maximum LLM cost in USD (> 0). The scan stops cleanly when this limit is reached. "
+            "Graduated wrap-up warnings are sent to all agents as it is approached."
+        ),
+    )
+
+    parser.add_argument(
+        "--max-turns",
+        dest="max_turns",
+        metavar="N",
+        type=_positive_int,
+        default=DEFAULT_MAX_TURNS,
+        help=(
+            "Maximum turns per agent (> 0, default %(default)s). Each agent is force-stopped "
+            "when it reaches this limit, with graduated wrap-up warnings as it is approached."
+        ),
     )
 
     parser.add_argument(
@@ -856,7 +902,7 @@ def display_completion_message(args: argparse.Namespace, results_path: Path) ->
     view_text = Text()
     view_text.append("\n")
     view_text.append("View", style="dim")
-    view_text.append("         ")
+    view_text.append("    ")
     view_text.append(f"strix view {args.run_name}", style="#22c55e")
     panel_parts.extend(["\n", view_text])
 
@@ -918,7 +964,7 @@ def pull_docker_image() -> None:
                 last_update = process_pull_line(line, layers_info, status, last_update)
 
         except DockerException as e:
-            logger.exception("Failed to pull docker image %s", image)
+            logger.debug("Failed to pull docker image %s", image, exc_info=True)
             console.print()
             error_text = Text()
             error_text.append("FAILED TO PULL IMAGE", style="bold red")

strix/interface/tui/app.py

@@ -15,6 +15,7 @@ from typing import TYPE_CHECKING, Any, ClassVar
 
 
 if TYPE_CHECKING:
+    from pygments.token import _TokenType
     from textual.timer import Timer
 
 from rich.align import Align
@@ -34,6 +35,7 @@ from textual.widgets.tree import TreeNode
 from strix.config import load_settings
 from strix.config.models import is_recommended_or_frontier_model
 from strix.core.hooks import BudgetExceededError
+from strix.core.inputs import DEFAULT_MAX_TURNS
 from strix.core.runner import run_strix_scan
 from strix.interface.tui.live_view import TuiLiveView
 from strix.interface.tui.messages import send_user_message_to_agent
@@ -351,7 +353,7 @@ class VulnerabilityDetailScreen(ModalScreen):  # type: ignore[misc]
                 if not token_value:
                     continue
                 color = None
-                tt = token_type
+                tt: _TokenType | None = token_type
                 while tt:
                     if tt in colors:
                         color = colors[tt]
@@ -814,6 +816,7 @@ class StrixTUIApp(App):  # type: ignore[misc]
         self._scan_completed = threading.Event()
         self._scan_error: BaseException | None = None
         self._error_noted_agents: set[str] = set()
+        self._budget_pause_notified = False
 
         self._spinner_frame_index: int = 0
         self._sweep_num_squares: int = 6
@@ -1038,14 +1041,15 @@ class StrixTUIApp(App):  # type: ignore[misc]
                             name=names.get(agent_id, agent_id),
                             parent_id=parent_of.get(agent_id),
                             status=status,
-                            error_message=error,
+                            error_message=error or "",
                         )
-                        if status in {"failed", "crashed"} and error:
+                        if error:
                             if agent_id not in self._error_noted_agents:
                                 self._error_noted_agents.add(agent_id)
                                 self.live_view.record_agent_error(agent_id, error)
                         else:
                             self._error_noted_agents.discard(agent_id)
+                    self._notify_budget_pause(statuses)
 
         if self._scan_loop is None or self._scan_loop.is_closed():
             return
@@ -1057,6 +1061,19 @@ class StrixTUIApp(App):  # type: ignore[misc]
 
         self._agent_graph_sync_future = asyncio.run_coroutine_threadsafe(collect(), self._scan_loop)
 
+    def _notify_budget_pause(self, statuses: dict[str, Any]) -> None:
+        paused = any(status == "budget_paused" for status in statuses.values())
+        if paused and not self._budget_pause_notified:
+            self._budget_pause_notified = True
+            self.notify(
+                "Budget limit reached \u2014 agents paused. Send a message to continue "
+                "(this extends the budget), or ctrl-q to quit.",
+                severity="warning",
+                timeout=15,
+            )
+        elif not paused:
+            self._budget_pause_notified = False
+
     def _update_agent_node(self, agent_id: str, agent_data: dict[str, Any]) -> bool:
         if agent_id not in self.agent_nodes:
             return False
@@ -1069,6 +1086,7 @@ class StrixTUIApp(App):  # type: ignore[misc]
             status_indicators = {
                 "running": "⚪",
                 "waiting": "⏸",
+                "budget_paused": "⏸",
                 "completed": "🟢",
                 "failed": "🔴",
                 "crashed": "🔴",
@@ -1266,10 +1284,21 @@ class StrixTUIApp(App):  # type: ignore[misc]
             self._stop_dot_animation()
             return (text, Text(), False)
 
-        if status == "waiting":
+        if status in {"waiting", "budget_paused"}:
             text = Text()
-            text.append("Send message to resume", style="dim")
-            return (text, Text(), False)
+            keymap = Text()
+            if status == "budget_paused":
+                text.append("Budget limit reached", style="yellow")
+                text.append(" \u00b7 ", style="dim")
+                text.append("Send a message to continue", style="dim")
+                keymap = keymap_styled([("ctrl-q", "quit")])
+            else:
+                error_msg = agent_data.get("error_message") or ""
+                if error_msg:
+                    text.append(error_msg, style="red")
+                    text.append(" \u00b7 ", style="dim")
+                text.append("Send message to resume", style="dim")
+            return (text, keymap, False)
 
         if status == "running":
             if self._agent_has_real_activity(agent_id):
@@ -1494,6 +1523,7 @@ class StrixTUIApp(App):  # type: ignore[misc]
                                 coordinator=self.coordinator,
                                 interactive=True,
                                 max_budget_usd=getattr(self.args, "max_budget_usd", None),
+                                max_turns=getattr(self.args, "max_turns", DEFAULT_MAX_TURNS),
                                 event_sink=self._capture_sdk_event,
                             ),
                         )
@@ -1501,10 +1531,7 @@ class StrixTUIApp(App):  # type: ignore[misc]
                 except (KeyboardInterrupt, asyncio.CancelledError):
                     logger.info("Scan interrupted by user")
                 except BudgetExceededError:
-                    # Defensive: the runner stops the scan cleanly on budget and
-                    # returns, so this normally never propagates. Treat it as a
-                    # graceful stop, not a scan error, if it ever does.
-                    logger.info("Scan stopped: --max-budget-usd limit reached")
+                    logger.info("Scan stopped: --max-budget limit reached")
                 except (ConnectionError, TimeoutError) as e:
                     logging.exception("Network error during scan")
                     self._scan_error = e
@@ -1559,6 +1586,7 @@ class StrixTUIApp(App):  # type: ignore[misc]
         status_indicators = {
             "running": "⚪",
             "waiting": "⏸",
+            "budget_paused": "⏸",
             "completed": "🟢",
             "failed": "🔴",
             "crashed": "🔴",
@@ -1605,6 +1633,7 @@ class StrixTUIApp(App):  # type: ignore[misc]
         status_indicators = {
             "running": "⚪",
             "waiting": "⏸",
+            "budget_paused": "⏸",
             "completed": "🟢",
             "failed": "🔴",
             "crashed": "🔴",
@@ -1729,7 +1758,10 @@ class StrixTUIApp(App):  # type: ignore[misc]
             message=message,
         )
         if not submitted:
-            self.notify("Scan loop is not ready; message was not sent", severity="warning")
+            if self._scan_completed.is_set():
+                self.notify("The scan has ended; message was not sent", severity="warning")
+            else:
+                self.notify("Scan loop is not ready; message was not sent", severity="warning")
             return
 
         self._displayed_events.clear()

strix/interface/tui/live_view.py

@@ -20,7 +20,7 @@ class TuiLiveView:
         self.events: list[dict[str, Any]] = []
         self._next_event_id = 1
         self._open_assistant_event_by_agent: dict[str, dict[str, Any]] = {}
-        self._tool_event_by_call_id: dict[str, dict[str, Any]] = {}
+        self._tool_event_by_agent_and_call_id: dict[tuple[str, str], dict[str, Any]] = {}
 
     def hydrate_from_run_dir(self, run_dir: Path) -> None:
         state_dir = runtime_state_dir(run_dir)
@@ -82,7 +82,7 @@ class TuiLiveView:
             current["parent_id"] = parent_id
         if status is not None:
             current["status"] = status
-        if error_message:
+        if error_message is not None:
             current["error_message"] = error_message
         current["updated_at"] = now
 
@@ -223,7 +223,8 @@ class TuiLiveView:
         timestamp: str | None = None,
     ) -> None:
         call_id = call["call_id"]
-        existing = self._tool_event_by_call_id.get(call_id)
+        event_key = (agent_id, call_id)
+        existing = self._tool_event_by_agent_and_call_id.get(event_key)
         tool_data = {
             "tool_name": call["tool_name"],
             "args": call["args"],
@@ -233,7 +234,7 @@ class TuiLiveView:
         }
         if existing is None:
             event = self._append_event(agent_id, "tool", tool_data, timestamp=timestamp)
-            self._tool_event_by_call_id[call_id] = event
+            self._tool_event_by_agent_and_call_id[event_key] = event
         else:
             existing["data"].update(tool_data)
             self._bump_event(existing, timestamp=timestamp)
@@ -249,7 +250,8 @@ class TuiLiveView:
         timestamp: str | None = None,
     ) -> None:
         call_id = output["call_id"]
-        event = self._tool_event_by_call_id.get(call_id)
+        event_key = (agent_id, call_id)
+        event = self._tool_event_by_agent_and_call_id.get(event_key)
         if event is None:
             event = self._append_event(
                 agent_id,
@@ -263,7 +265,7 @@ class TuiLiveView:
                 },
                 timestamp=timestamp,
             )
-            self._tool_event_by_call_id[call_id] = event
+            self._tool_event_by_agent_and_call_id[event_key] = event
 
         result = _parse_json_value(output["output"])
         event["data"]["result"] = result

strix/interface/tui/renderers/__init__.py

@@ -6,6 +6,7 @@ from . import (
     notes_renderer,
     proxy_renderer,
     reporting_renderer,
+    respond_renderer,
     shell_renderer,
     thinking_renderer,
     todo_renderer,
@@ -23,6 +24,7 @@ __all__ = [
     "proxy_renderer",
     "render_tool_widget",
     "reporting_renderer",
+    "respond_renderer",
     "shell_renderer",
     "thinking_renderer",
     "todo_renderer",

strix/interface/tui/renderers/agents_graph_renderer.py

@@ -117,8 +117,8 @@ class AgentFinishRenderer(BaseToolRenderer):
 
 
 @register_tool_renderer
-class WaitForMessageRenderer(BaseToolRenderer):
-    tool_name: ClassVar[str] = "wait_for_message"
+class WaitForAgentsRenderer(BaseToolRenderer):
+    tool_name: ClassVar[str] = "wait_for_agents"
     css_classes: ClassVar[list[str]] = ["tool-call", "agents-graph-tool"]
 
     @classmethod

strix/interface/tui/renderers/respond_renderer.py

@@ -0,0 +1,35 @@
+from typing import Any, ClassVar
+
+from rich.text import Text
+from textual.widgets import Static
+
+from .agent_message_renderer import AgentMessageRenderer
+from .base_renderer import BaseToolRenderer
+from .registry import register_tool_renderer
+
+
+@register_tool_renderer
+class RespondToUserRenderer(BaseToolRenderer):
+    """Render a reply as the agent's own prose, not as a tool call.
+
+    ``respond_to_user`` carries the message the user is meant to read, so it
+    gets the same markdown treatment as a plain assistant turn.
+    """
+
+    tool_name: ClassVar[str] = "respond_to_user"
+    css_classes: ClassVar[list[str]] = ["tool-call", "respond-tool"]
+
+    @classmethod
+    def render(cls, tool_data: dict[str, Any]) -> Static:
+        args = tool_data.get("args", {})
+        message = args.get("message", "")
+
+        text = Text()
+        if message:
+            text.append_text(AgentMessageRenderer.render_simple(message))
+            text.append("\n\n")
+        text.append("○ ", style="#6b7280")
+        text.append("waiting for your reply", style="dim")
+
+        css_classes = cls.get_css_classes(tool_data.get("status", "unknown"))
+        return Static(text, classes=css_classes)

strix/interface/update_check.py

@@ -271,7 +271,13 @@ def _release_target() -> str | None:
     if os_name is None:
         return None
     target = f"{os_name}-{arch}"
-    supported = {"linux-x86_64", "macos-x86_64", "macos-arm64", "windows-x86_64"}
+    supported = {
+        "linux-x86_64",
+        "linux-arm64",
+        "macos-x86_64",
+        "macos-arm64",
+        "windows-x86_64",
+    }
     return target if target in supported else None
 
 

strix/interface/utils.py

@@ -11,11 +11,10 @@ import tempfile
 from dataclasses import dataclass, field
 from pathlib import Path
 from typing import Any
-from urllib.error import HTTPError, URLError
 from urllib.parse import urlparse
-from urllib.request import Request, urlopen
 
 import docker
+import requests
 from docker.errors import DockerException, ImageNotFound
 from rich.console import Console
 from rich.panel import Panel
@@ -1088,13 +1087,12 @@ def resolve_diff_scope_context(
 def _is_http_git_repo(url: str) -> bool:
     check_url = f"{url.rstrip('/')}/info/refs?service=git-upload-pack"
     try:
-        req = Request(check_url, headers={"User-Agent": "git/strix"})  # noqa: S310
-        with urlopen(req, timeout=10) as resp:  # noqa: S310  # nosec B310
-            return "x-git-upload-pack-advertisement" in resp.headers.get("Content-Type", "")
-    except HTTPError as e:
-        return e.code == 401
-    except (URLError, OSError, ValueError):
+        resp = requests.get(check_url, headers={"User-Agent": "git/strix"}, timeout=10)
+    except (requests.RequestException, ValueError):
         return False
+    if resp.status_code >= 400:
+        return resp.status_code == 401
+    return "x-git-upload-pack-advertisement" in resp.headers.get("Content-Type", "")
 
 
 def infer_target_type(target: str) -> tuple[str, dict[str, str]]:  # noqa: PLR0911

strix/interface/viewer/auth.py

@@ -15,12 +15,12 @@ import base64
 import contextlib
 import json
 import logging
-import urllib.error
-import urllib.request
 from datetime import UTC, datetime
 from pathlib import Path
 from typing import Any
 
+import requests
+
 from strix.config.loader import load_settings
 
 
@@ -147,21 +147,17 @@ def _post_json(path: str, payload: dict[str, Any], *, timeout: int) -> tuple[int
     map, not raised.
     """
     url = f"{_app_url()}{path}"
-    body = json.dumps(payload).encode("utf-8")
-    request = urllib.request.Request(  # noqa: S310 - fixed https relay URL
-        url,
-        data=body,
-        headers={"Content-Type": "application/json", "Accept": "application/json"},
-        method="POST",
-    )
     try:
-        with urllib.request.urlopen(request, timeout=timeout) as response:  # noqa: S310  # nosec B310
-            return response.status, _parse_body(response.read())
-    except urllib.error.HTTPError as exc:
-        return exc.code, _parse_body(exc.read())
-    except (urllib.error.URLError, TimeoutError, OSError) as exc:
+        response = requests.post(
+            url,
+            json=payload,
+            headers={"Accept": "application/json"},
+            timeout=timeout,
+        )
+    except requests.RequestException as exc:
         logger.warning("relay request to %s failed: %s", path, exc)
         raise RelayError("unavailable") from exc
+    return response.status_code, _parse_body(response.content)
 
 
 def _parse_body(raw: bytes) -> dict[str, Any]:

strix/interface/viewer/frontend/src/components/live/tool-renderers/AgentCommsRenderer.tsx

@@ -54,7 +54,7 @@ export default function AgentCommsRenderer({ toolName, args }: ToolRendererProps
     );
   }
 
-  if (toolName === "wait_for_message") {
+  if (toolName === "wait_for_agents") {
     const reason = (args.reason as string) ?? "";
     return (
       <div className="flex items-center gap-2">

strix/interface/viewer/frontend/src/components/live/tool-renderers/RespondRenderer.tsx

@@ -0,0 +1,20 @@
+"use client";
+
+import type { ToolRendererProps } from "@/types/events";
+import Markdown from "./Markdown";
+
+/**
+ * `respond_to_user` carries the message the user is meant to read, so it renders
+ * as the agent's own prose rather than as a tool call.
+ */
+export default function RespondRenderer({ args }: ToolRendererProps) {
+  const message = (args.message as string) ?? "";
+  if (!message) return null;
+
+  return (
+    <div>
+      <Markdown text={message} />
+      <div className="mt-1.5 text-[#888] text-[13px]">waiting for your reply</div>
+    </div>
+  );
+}

strix/interface/viewer/frontend/src/components/live/tool-renderers/index.ts

@@ -24,6 +24,7 @@ import NotesRenderer from "./NotesRenderer";
 import TodoRenderer from "./TodoRenderer";
 import FallbackRenderer from "./FallbackRenderer";
 import LoadSkillRenderer from "./LoadSkillRenderer";
+import RespondRenderer from "./RespondRenderer";
 
 /**
  * Tool-renderer mapping — data-driven, keyed by the engine's tool *family*.
@@ -104,10 +105,10 @@ const CATEGORY_TOOLS: Record<ToolCategory, readonly string[]> = {
   proxy: ["list_requests", "view_request", "repeat_request", "list_sitemap", "view_sitemap_entry", "scope_rules", "send_request"],
   reporting: ["create_vulnerability_report", "list_reports", "get_report"],
   thinking: ["think"],
-  agents: ["create_agent", "agent_finish", "send_message_to_agent", "wait_for_message", "view_agent_graph", "stop_agent"],
+  agents: ["create_agent", "agent_finish", "send_message_to_agent", "wait_for_agents", "view_agent_graph", "stop_agent"],
   search: ["web_search"],
   // scan_start_info / subagent_start_info are strix-app synthetic events; finish_scan is the engine's
-  lifecycle: ["scan_start_info", "subagent_start_info", "finish_scan"],
+  lifecycle: ["scan_start_info", "subagent_start_info", "finish_scan", "respond_to_user"],
   notes: ["create_note", "delete_note", "update_note", "list_notes", "get_note"],
   skills: ["load_skill"],
   todos: ["create_todo", "list_todos", "update_todo", "mark_todo_done", "mark_todo_pending", "delete_todo"],
@@ -127,6 +128,7 @@ const TOOL_CATEGORY: Record<string, ToolCategory> = Object.fromEntries(
  */
 const RENDERER_OVERRIDES: Partial<Record<string, ComponentType<ToolRendererProps>>> = {
   finish_scan: FinishRenderer,
+  respond_to_user: RespondRenderer,
   apply_patch: ApplyPatchRenderer,
   view_image: ViewImageRenderer,
   list_reports: ReportListRenderer,
@@ -140,7 +142,8 @@ const RENDERER_OVERRIDES: Partial<Record<string, ComponentType<ToolRendererProps
 const ICON_OVERRIDES: Partial<Record<string, ToolIconMeta>> = {
   agent_finish: { icon: Flag, color: "text-cyan-400" },
   send_message_to_agent: { icon: MessageCircle, color: "text-cyan-400" },
-  wait_for_message: { icon: MessageCircle, color: "text-cyan-400" },
+  wait_for_agents: { icon: MessageCircle, color: "text-cyan-400" },
+  respond_to_user: { icon: MessageCircle, color: "text-emerald-400" },
   view_agent_graph: { icon: Eye, color: "text-cyan-400" },
   stop_agent: { icon: Ban, color: "text-red-400" },
   scan_start_info: { icon: Crosshair, color: "text-emerald-400" },

strix/interface/viewer/server.py

@@ -107,8 +107,11 @@ def resolve_run_dir(base_dir: Path, run_param: str | None, default_run_dir: Path
     return candidate
 
 
-# Name of the cookie carrying the per-process session capability.
-SESSION_COOKIE = "strix_viewer_session"
+# Prefix of the cookie carrying the per-process session capability. The bound
+# port is appended (``strix_viewer_session_<port>``) because browsers scope
+# cookies by host only, never by port: concurrent viewers on 127.0.0.1 would
+# otherwise share one cookie slot and clobber each other's session.
+SESSION_COOKIE_PREFIX = "strix_viewer_session"
 
 
 class _ViewerState:
@@ -135,6 +138,9 @@ class _ViewerState:
         # enough to steer a live scan, trigger a report, or browse history --
         # the token is never handed to a caller who merely reaches ``/``.
         self.session_token = secrets.token_urlsafe(32)
+        # Finalized in ``serve()`` once the port is known (the server binds
+        # after this state is constructed); see SESSION_COOKIE_PREFIX.
+        self.cookie_name = SESSION_COOKIE_PREFIX
 
 
 def _make_handler(state: _ViewerState) -> type[BaseHTTPRequestHandler]:
@@ -476,7 +482,7 @@ def _make_handler(state: _ViewerState) -> type[BaseHTTPRequestHandler]:
             the browser this process handed the page to can pass. A direct
             caller on an exposed port has no cookie and is rejected.
             """
-            supplied = self._cookies().get(SESSION_COOKIE, "")
+            supplied = self._cookies().get(state.cookie_name, "")
             return bool(supplied) and secrets.compare_digest(supplied, state.session_token)
 
         def _token_presented(self, query: dict[str, list[str]]) -> bool:
@@ -512,7 +518,7 @@ def _make_handler(state: _ViewerState) -> type[BaseHTTPRequestHandler]:
                 # SameSite=Strict (never sent from a cross-site context).
                 self.send_header(
                     "Set-Cookie",
-                    f"{SESSION_COOKIE}={state.session_token}; Path=/; HttpOnly; SameSite=Strict",
+                    f"{state.cookie_name}={state.session_token}; Path=/; HttpOnly; SameSite=Strict",
                 )
             self.end_headers()
             self.wfile.write(content)
@@ -586,6 +592,7 @@ def serve(
 
     httpd.daemon_threads = True
     bound_port = int(httpd.server_address[1])
+    state.cookie_name = f"{SESSION_COOKIE_PREFIX}_{bound_port}"
     url = f"http://{host}:{bound_port}"
 
     thread = threading.Thread(target=httpd.serve_forever, name="strix-viewer", daemon=True)

strix/interface/viewer/static/index.html

@@ -6,7 +6,7 @@
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
     <meta name="color-scheme" content="dark" />
     <title>Strix Results</title>
-    <script type="module" crossorigin src="./assets/index-DzvI_0HX.js"></script>
+    <script type="module" crossorigin src="./assets/index-CGvQq6oe.js"></script>
     <link rel="stylesheet" crossorigin href="./assets/index-C3kQ5kk8.css">
   </head>
   <body>

strix/llm/compaction.py

@@ -12,15 +12,20 @@ from __future__ import annotations
 import logging
 from typing import TYPE_CHECKING, Any
 
-import litellm
+from agents.model_settings import ModelSettings
+from agents.models.interface import ModelTracing
 from litellm.exceptions import BadRequestError, ContextWindowExceededError
+from openai.types.responses import ResponseOutputMessage, ResponseOutputText
 
 from strix.config import load_settings
+from strix.config.models import StrixProvider
+from strix.core.inputs import make_model_settings
 from strix.core.sessions import replace_session_items, session_write_lock
 from strix.llm.context_budget import context_window, count_tokens, output_limit
 
 
 if TYPE_CHECKING:
+    from agents.items import ModelResponse
     from agents.memory import Session
 
 
@@ -268,26 +273,53 @@ def _checkpoint_item(summary: str) -> dict[str, Any]:
     }
 
 
+def _extract_text(response: ModelResponse) -> str:
+    parts: list[str] = []
+    for item in response.output:
+        if not isinstance(item, ResponseOutputMessage):
+            continue
+        parts.extend(
+            chunk.text
+            for chunk in item.content
+            if isinstance(chunk, ResponseOutputText) and chunk.text
+        )
+    return "".join(parts)
+
+
 async def _summarize(model: str, prompt: str, max_tokens: int) -> str | None:
     llm = load_settings().llm
+    model_settings = make_model_settings(
+        None,
+        model_name=model,
+        request_timeout=llm.timeout,
+        prompt_cache=False,
+        extra_headers=llm.extra_headers,
+    ).resolve(ModelSettings(max_tokens=max_tokens))
     try:
-        response = await litellm.acompletion(
-            model=model,
-            messages=[{"role": "user", "content": prompt}],
-            max_tokens=max_tokens,
-            api_key=llm.api_key,
-            api_base=llm.api_base,
-            timeout=llm.timeout,
+        response = (
+            await StrixProvider()
+            .get_model(model)
+            .get_response(
+                system_instructions=None,
+                input=prompt,
+                model_settings=model_settings,
+                tools=[],
+                output_schema=None,
+                handoffs=[],
+                tracing=ModelTracing.DISABLED,
+                previous_response_id=None,
+                conversation_id=None,
+                prompt=None,
+            )
         )
     except Exception:
         logger.exception("compaction summary call failed for model %s", model)
         return None
-    try:
-        content = response.choices[0].message.content
-    except (AttributeError, IndexError, KeyError):
+    content = _extract_text(response).strip()
+    if not content:
         logger.warning("compaction summary returned no content")
         return None
-    return content.strip() if isinstance(content, str) and content.strip() else None
+    return content
 
 
 async def maybe_compact(

strix/llm/context_budget.py

@@ -17,7 +17,14 @@ logger = logging.getLogger(__name__)
 
 # LiteLLM keys models without the routing prefix users type (``openai/``,
 # ``litellm/``, ``ollama/`` ...). Strip a leading provider segment on lookup.
-_STRIPPABLE_PREFIXES = ("openai/", "litellm/", "any-llm/", "ollama/", "ollama_chat/")
+_STRIPPABLE_PREFIXES = (
+    "openai/",
+    "chatgpt/",
+    "litellm/",
+    "any-llm/",
+    "ollama/",
+    "ollama_chat/",
+)
 
 _DEFAULT_OUTPUT_TOKENS = 8_192
 
@@ -38,7 +45,11 @@ def _safe_get_model_info(model: str) -> dict[str, Any] | None:
 
 @lru_cache(maxsize=128)
 def _model_info(model: str) -> dict[str, int]:
-    for candidate in (model, _lookup_key(model)):
+    lookup_key = _lookup_key(model)
+    # Provider-qualified ChatGPT lookups may start a synchronous device-login
+    # poll. LiteLLM keys the metadata by the underlying model slug.
+    candidates = (lookup_key,) if model.startswith("chatgpt/") else (model, lookup_key)
+    for candidate in candidates:
         info = _safe_get_model_info(candidate)
         if info is not None:
             return {

strix/report/dedupe.py

@@ -51,17 +51,24 @@ def _dedupe_extra_args(dedupe: DedupeSettings) -> dict[str, str]:
 def _dedupe_model_settings(
     dedupe: DedupeSettings, model_name: str, request_timeout: float | None
 ) -> ModelSettings:
+    llm = load_settings().llm
     settings = make_model_settings(
         dedupe.reasoning_effort,
         model_name=model_name,
         force_required_tool_choice=False,
         request_timeout=request_timeout,
+        # The main model's headers apply only when dedupe falls back to the main
+        # model; a dedicated dedupe model may route to another provider, which
+        # must never receive the main endpoint's credentials. A dedicated model
+        # gets its own DEDUPE_LLM_EXTRA_HEADERS instead.
+        extra_headers=dedupe.extra_headers if dedupe.model else llm.extra_headers,
     )
     extra = _dedupe_extra_args(dedupe)
     if extra:
         settings = settings.resolve(ModelSettings(extra_args=extra))
     return settings
 
+
 DEDUPE_SYSTEM_PROMPT = """You are an expert vulnerability report deduplication judge.
 Your task is to determine if a candidate vulnerability report describes the SAME vulnerability
 as any existing report.
@@ -347,9 +354,7 @@ async def check_duplicate(
         response = await model.get_response(
             system_instructions=DEDUPE_SYSTEM_PROMPT,
             input=user_msg,
-            model_settings=_dedupe_model_settings(
-                dedupe, resolved_model, settings.llm.timeout
-            ),
+            model_settings=_dedupe_model_settings(dedupe, resolved_model, settings.llm.timeout),
             tools=[],
             output_schema=None,
             handoffs=[],

strix/report/state.py

@@ -1,6 +1,7 @@
 import json
 import logging
 import subprocess
+import threading
 from collections.abc import Callable
 from datetime import UTC, datetime
 from importlib.metadata import PackageNotFoundError, version
@@ -95,6 +96,8 @@ def get_global_report_state() -> Optional["ReportState"]:
 def set_global_report_state(report_state: "ReportState") -> None:
     global _global_report_state  # noqa: PLW0603
     _global_report_state = report_state
+    # New run: drop any streamed-cost entries a prior run left unconsumed.
+    streamed_openrouter_costs.clear()
 
 
 class ReportState:
@@ -507,6 +510,72 @@ class ReportState:
         self._sync_llm_usage_record()
 
 
+def openrouter_stream_cost(usage: Any) -> float | None:
+    """Total OpenRouter-reported cost from a raw stream ``usage`` block, or None.
+
+    Non-BYOK responses bill everything to ``usage.cost``. BYOK responses put the
+    OpenRouter fee in ``usage.cost`` (often 0) and the provider charge in
+    ``usage.cost_details.upstream_inference_cost``, so BYOK totals sum the two.
+    """
+    if not isinstance(usage, dict):
+        return None
+    total = 0.0
+    cost = usage.get("cost")
+    if isinstance(cost, int | float) and cost > 0:
+        total += float(cost)
+    if bool(usage.get("is_byok")):
+        details = usage.get("cost_details")
+        upstream = details.get("upstream_inference_cost") if isinstance(details, dict) else None
+        if isinstance(upstream, int | float) and upstream > 0:
+            total += float(upstream)
+    return total if total > 0 else None
+
+
+def _response_id(completion_response: Any) -> str | None:
+    response_id = getattr(completion_response, "id", None)
+    if response_id is None and isinstance(completion_response, dict):
+        response_id = cast("dict[str, Any]", completion_response).get("id")
+    return response_id if isinstance(response_id, str) and response_id else None
+
+
+class StreamedOpenRouterCosts:
+    """Correlates OpenRouter's per-stream cost from the parser to the cost callback.
+
+    LiteLLM rebuilds streamed responses from token-only chunks and drops the
+    ``usage.cost`` OpenRouter reports in its final stream chunk (its non-streamed
+    path preserves it; streaming snapshots hidden params at stream start). Every
+    scan streams, so the OpenRouter streaming handler (see strix.config.models)
+    records the cost here keyed by response id, and the callback takes it back out
+    for the matching rebuilt response. Entries are removed on read; ``clear()``
+    runs per scan so nothing accumulates across runs.
+    """
+
+    def __init__(self) -> None:
+        self._costs: dict[str, float] = {}
+        self._lock = threading.Lock()
+
+    def remember(self, response_id: Any, usage: Any) -> None:
+        cost = openrouter_stream_cost(usage)
+        if cost is None or not (isinstance(response_id, str) and response_id):
+            return
+        with self._lock:
+            self._costs[response_id] = cost
+
+    def take(self, completion_response: Any) -> float | None:
+        response_id = _response_id(completion_response)
+        if response_id is None:
+            return None
+        with self._lock:
+            return self._costs.pop(response_id, None)
+
+    def clear(self) -> None:
+        with self._lock:
+            self._costs.clear()
+
+
+streamed_openrouter_costs = StreamedOpenRouterCosts()
+
+
 def litellm_cost_callback(
     kwargs: Any,
     completion_response: Any,
@@ -541,6 +610,11 @@ def litellm_cost_callback(
     if cost is None:
         cost = _usage_reported_cost(completion_response)
 
+    # Recover the exact OpenRouter cost the streaming handler stashed for this
+    # response — LiteLLM drops it from streamed usage, so nothing above sees it.
+    if cost is None:
+        cost = streamed_openrouter_costs.take(completion_response)
+
     if cost is None:
         cost = _estimate_response_cost(kwargs, completion_response)
 

strix/runtime/docker_client.py

@@ -110,6 +110,19 @@ def _apply_log_limits(create_kwargs: dict[str, Any]) -> None:
     )
 
 
+def _apply_run_labels(create_kwargs: dict[str, Any]) -> None:
+    run_id = os.getenv("STRIX_RUN_ID")
+    if not run_id:
+        return
+    labels = create_kwargs.setdefault("labels", {})
+    if not isinstance(labels, dict):
+        return
+    labels["strix-run-id"] = run_id
+    run_type = os.getenv("STRIX_RUN_TYPE")
+    if run_type:
+        labels["strix-run-type"] = run_type
+
+
 class StrixDockerSandboxSession(DockerSandboxSession):
     sandbox_network: str = ""
 
@@ -222,6 +235,7 @@ class StrixDockerSandboxClient(DockerSandboxClient):
         _apply_sandbox_network(create_kwargs)
         _apply_resource_limits(create_kwargs)
         _apply_log_limits(create_kwargs)
+        _apply_run_labels(create_kwargs)
 
         # Strix injection: host bind mounts (e.g. large repos passed via --mount)
         # that bypass the SDK's file-by-file LocalDir copy.

strix/telemetry/posthog.py

@@ -1,9 +1,9 @@
-import json
 import logging
-import urllib.request
 from datetime import datetime
 from typing import TYPE_CHECKING, Any
 
+import requests
+
 from strix.config import load_settings
 from strix.telemetry._common import (
     SESSION_ID,
@@ -37,13 +37,7 @@ def _send(event: str, properties: dict[str, Any]) -> bool:
             "distinct_id": SESSION_ID,
             "properties": properties,
         }
-        req = urllib.request.Request(  # noqa: S310
-            f"{_POSTHOG_HOST}/capture/",
-            data=json.dumps(payload).encode(),
-            headers={"Content-Type": "application/json"},
-        )
-        with urllib.request.urlopen(req, timeout=10):  # noqa: S310  # nosec B310
-            pass
+        requests.post(f"{_POSTHOG_HOST}/capture/", json=payload, timeout=10)
     except Exception:  # noqa: BLE001
         logger.debug("posthog send failed for event %s", event, exc_info=True)
         return False

strix/telemetry/scarf.py

@@ -2,10 +2,11 @@ from __future__ import annotations
 
 import logging
 import urllib.parse
-import urllib.request
 from datetime import datetime
 from typing import TYPE_CHECKING, Any
 
+import requests
+
 from strix.config import load_settings
 from strix.telemetry._common import (
     SESSION_ID,
@@ -42,9 +43,7 @@ def _send(event: str, properties: dict[str, Any]) -> bool:
         url = f"{_SCARF_ENDPOINT}{path}"
         if query:
             url = f"{url}?{query}"
-        req = urllib.request.Request(url, method="POST")  # noqa: S310
-        with urllib.request.urlopen(req, timeout=10):  # noqa: S310  # nosec B310
-            pass
+        requests.post(url, timeout=10)
     except Exception:  # noqa: BLE001
         logger.debug("scarf send failed for event %s", event, exc_info=True)
         return False

strix/tools/agents_graph/tools.py

@@ -218,25 +218,43 @@ def _session_items_payload(items: list[Any]) -> list[dict[str, Any]]:
     return payload
 
 
-@function_tool(timeout=601)
-async def wait_for_message(  # noqa: PLR0911
+_WAIT_DEFAULT_TIMEOUT_S = 300
+# Enforced by the SDK around the whole tool call, so it caps an oversized
+# ``timeout_seconds`` the model asks for. One second of headroom lets the
+# tool's own timeout fire first and return a clean result.
+_WAIT_HARD_CEILING_S = _WAIT_DEFAULT_TIMEOUT_S + 1
+
+
+@function_tool(timeout=_WAIT_HARD_CEILING_S)
+async def wait_for_agents(  # noqa: PLR0911
     ctx: RunContextWrapper,
     reason: str = "Waiting for messages from other agents",
-    timeout_seconds: int = 600,
+    timeout_seconds: int = _WAIT_DEFAULT_TIMEOUT_S,
 ) -> str:
-    """Pause this agent until a message lands in its inbox (or timeout).
+    """Pause until another AGENT messages you (or the timeout elapses).
 
-    Use when you have nothing useful to do until a child/peer responds
-    — typically after spawning subagents and you want to wait for
-    their completion reports. The agent automatically resumes when any
-    message arrives, so pick a ``timeout_seconds`` proportional to the
-    work you're awaiting.
+    Use when you have nothing useful to do until a child or peer
+    responds — typically after spawning subagents and you want their
+    completion reports. You resume the instant any message arrives, so
+    size ``timeout_seconds`` to the work you're awaiting.
+
+    **This tool is only for waiting on other agents.** Two things it is
+    NOT for:
+
+    - **Talking to the user.** Use ``respond_to_user``, which delivers
+      your message and hands control back in one call.
+    - **Waiting for a long-running command.** This tool does not watch
+      processes at all — it sleeps until a *message* arrives, so it
+      burns the full timeout even if your command finished a second
+      later. Poll the process instead: ``exec_command`` returns a
+      session/process id, and ``write_stdin`` with ``chars=""`` returns
+      as soon as there is new output or the process exits.
 
     **Critical caveats:**
 
-    - **Never** call this if you finished your own task and have **no**
-      child agents running — that's a permanent stall. Call
-      ``finish_scan`` (root) or ``agent_finish`` (subagent) instead.
+    - **Never** call this if you have no agents left to hear from —
+      that just strands you until the timeout. Call ``finish_scan``
+      (root) or ``agent_finish`` (subagent) instead.
     - If you're waiting on an agent that **isn't your child**, message
       it first asking it to ping you when done — otherwise it has no
       reason to send to your inbox and you'll wait the full timeout.
@@ -247,7 +265,8 @@ async def wait_for_message(  # noqa: PLR0911
         reason: One-line note shown in graph snapshots while you're
             waiting (helps a human or sibling agent debug who's stuck
             on what).
-        timeout_seconds: Max seconds to wait (default 600). This is only
+        timeout_seconds: Max seconds to wait (default 300, and values above
+            that are cut short by a hard ceiling). This is only
             a cap — the tool returns the INSTANT a message arrives, so a
             larger value never makes you wait longer when the reply does
             come. Right-size it to what you're waiting on: a short wait
@@ -257,9 +276,7 @@ async def wait_for_message(  # noqa: PLR0911
             bites when the expected message never arrives — so an oversized
             timeout on a trivial wait just strands you idle until it
             elapses. On timeout the tool returns and you decide whether to
-            keep working or wait again. (Applies to autonomous multi-agent
-            runs; in interactive/chat sessions the agent instead parks until
-            a message arrives and this cap is not enforced.)
+            keep working or wait again.
     """
     inner = _ctx(ctx)
     coordinator = coordinator_from_context(inner)
@@ -302,7 +319,7 @@ async def wait_for_message(  # noqa: PLR0911
         )
 
     if interactive:
-        await coordinator.park_waiting(me)
+        await coordinator.park_waiting(me, wait_kind="agents")
         return json.dumps(
             {
                 "success": True,
@@ -314,7 +331,7 @@ async def wait_for_message(  # noqa: PLR0911
             default=str,
         )
 
-    await coordinator.park_waiting(me)
+    await coordinator.park_waiting(me, wait_kind="agents")
     try:
         await asyncio.wait_for(coordinator.wait_for_message(me), timeout_seconds)
     except TimeoutError:
@@ -373,7 +390,7 @@ async def create_agent(
 
     Decompose complex pentests by handing focused subtasks to dedicated
     children. The child runs asynchronously — the parent continues
-    immediately and can ``wait_for_message`` later (or just keep
+    immediately and can ``wait_for_agents`` later (or just keep
     working in parallel). When the child calls ``agent_finish``, its
     completion report lands in the parent's inbox.
 

strix/tools/finish/tool.py

@@ -101,7 +101,7 @@ async def finish_scan(
     execution stops. There is no draft mode and no second chance: never
     submit placeholder, provisional, or "checking if done" text in any
     field, and never call ``finish_scan`` to poll whether subagents are
-    done (use ``view_agent_graph`` / ``wait_for_message`` for that).
+    done (use ``view_agent_graph`` / ``wait_for_agents`` for that).
     Call it exactly ONCE, only when every field holds genuine, finished
     assessment prose.
 
@@ -111,7 +111,7 @@ async def finish_scan(
        summary. If ANY agent is in ``running`` / ``waiting`` state,
        you MUST NOT call ``finish_scan`` yet —
        wrap them up first via ``send_message_to_agent`` (ask them to
-       finish), ``wait_for_message`` (block until their report
+       finish), ``wait_for_agents`` (block until their report
        arrives), or ``stop_agent`` (graceful cancel). Only ``completed``
        / ``crashed`` / ``stopped`` agents are safe to leave behind.
        Calling ``finish_scan`` while children are alive orphans their
@@ -253,6 +253,8 @@ async def finish_scan(
     parent_id = inner.get("parent_id")
     if coordinator is not None and parent_id is None and me is not None:
         active_agents = await coordinator.active_agents_except(me)
+        if active_agents and coordinator.reserve_stopped:
+            active_agents = []
     else:
         active_agents = []
 

strix/tools/respond/__init__.py

@@ -0,0 +1,6 @@
+"""User-facing reply tool for interactive sessions."""
+
+from strix.tools.respond.tool import respond_to_user
+
+
+__all__ = ["respond_to_user"]

strix/tools/respond/tool.py

@@ -0,0 +1,110 @@
+"""``respond_to_user`` — deliver a reply and hand control back to the user."""
+
+from __future__ import annotations
+
+import json
+from typing import Any
+
+from agents import RunContextWrapper, function_tool
+
+from strix.core.agents import coordinator_from_context
+
+
+def _ctx(ctx: RunContextWrapper) -> dict[str, Any]:
+    return ctx.context if isinstance(ctx.context, dict) else {}
+
+
+@function_tool
+async def respond_to_user(ctx: RunContextWrapper, message: str) -> str:
+    """Answer the user and hand control back to them.
+
+    This is the ONLY way to yield to the user. Delivering the message and
+    yielding are the same call on purpose: there is no way to answer and
+    then forget to stop, and no way to stop without having answered.
+
+    Call it when you have something for the user and nothing to do until
+    they reply — you answered their question, you need a decision or a
+    credential only they can give, or you finished a chunk of work and
+    want direction. You resume exactly where you left off when they
+    reply, with everything you have done so far intact.
+
+    Do NOT call it to narrate progress or to think out loud. Plain text
+    is still shown to the user as you work, so say whatever you like
+    mid-task without stopping; ``respond_to_user`` is specifically the
+    act of *waiting* for them. Every call costs the user their attention.
+
+    Not for these:
+
+    - **Waiting on another agent** (a child's report, a peer's reply) —
+      use ``wait_for_agents``.
+    - **Ending the engagement** — use ``finish_scan`` (root) or
+      ``agent_finish`` (subagent). Those are terminal; this is a pause.
+
+    Args:
+        message: What to say to the user. Self-contained: they may not
+            have followed the tool calls that led here. Lead with the
+            answer or the decision you need, and if you are blocked, say
+            exactly what you need from them.
+    """
+    inner = _ctx(ctx)
+    coordinator = coordinator_from_context(inner)
+    me = inner.get("agent_id")
+    interactive = bool(inner.get("interactive", False))
+
+    if coordinator is None or me is None:
+        return json.dumps(
+            {"success": False, "error": "Agent coordinator or agent_id missing in context"},
+            ensure_ascii=False,
+            default=str,
+        )
+
+    if not interactive:
+        return json.dumps(
+            {
+                "success": False,
+                "error": (
+                    "No user is attached to an autonomous run. Keep working, and call "
+                    "finish_scan (root) or agent_finish (subagent) when the task is done."
+                ),
+            },
+            ensure_ascii=False,
+            default=str,
+        )
+
+    async with coordinator._lock:
+        stopped = coordinator.statuses.get(me) == "stopped"
+    if stopped:
+        return json.dumps(
+            {"success": True, "wait_outcome": "stopped", "message": message},
+            ensure_ascii=False,
+            default=str,
+        )
+
+    # A message that arrived while this turn was running is the user already
+    # talking: take it now instead of parking for one they have sent.
+    pending, _ = await coordinator.consume_pending(me)
+    if pending > 0:
+        await coordinator.mark_running(me)
+        return json.dumps(
+            {
+                "success": True,
+                "wait_outcome": "message_arrived",
+                "pending_messages": pending,
+                "message": message,
+                "note": "Your reply was delivered; the user had already sent a new message.",
+            },
+            ensure_ascii=False,
+            default=str,
+        )
+
+    await coordinator.park_waiting(me, wait_kind="user")
+    return json.dumps(
+        {
+            "success": True,
+            "wait_outcome": "waiting",
+            "message": message,
+            "note": "Reply delivered; parked until the user responds.",
+        },
+        ensure_ascii=False,
+        default=str,
+    )

tests/test_agent_tool_registration.py

@@ -2,18 +2,29 @@
 
 from __future__ import annotations
 
+from typing import TYPE_CHECKING, Any
+
 import pytest
 from agents.tool import FunctionTool
 
 from strix.agents import factory
 
 
+if TYPE_CHECKING:
+    from agents.tool_context import ToolContext
+
+
 def _tool(name: str) -> FunctionTool:
+    # A per-tool closure keeps two same-named tools unequal, which is what the
+    # duplicate-name tests exercise.
+    async def invoke(_ctx: ToolContext[Any], _input: str) -> str:
+        return "ok"
+
     return FunctionTool(
         name=name,
         description="test tool",
         params_json_schema={"type": "object", "properties": {}, "additionalProperties": False},
-        on_invoke_tool=lambda _ctx, _inp: "ok",
+        on_invoke_tool=invoke,
     )
 
 
@@ -86,3 +97,18 @@ def test_no_override_renders_builtin_prompt() -> None:
 
     assert isinstance(agent.instructions, str)
     assert agent.instructions != ""
+
+
+def test_respond_to_user_is_interactive_only() -> None:
+    """Yielding to the user is meaningless when no user is attached."""
+    interactive = factory.build_strix_agent(is_root=True, interactive=True)
+    autonomous = factory.build_strix_agent(is_root=True, interactive=False)
+
+    assert "respond_to_user" in [t.name for t in interactive.tools]
+    assert "respond_to_user" not in [t.name for t in autonomous.tools]
+
+
+def test_wait_for_agents_is_available_in_both_modes() -> None:
+    for interactive in (True, False):
+        agent = factory.build_strix_agent(is_root=True, interactive=interactive)
+        assert "wait_for_agents" in [t.name for t in agent.tools]

tests/test_codex_auth.py

@@ -7,8 +7,10 @@ import hashlib
 import json
 import time
 from typing import TYPE_CHECKING, Any
+from unittest import mock
 
 import pytest
+import requests
 
 from strix.config import codex
 
@@ -52,6 +54,18 @@ def test_authorize_url_carries_pkce_and_client() -> None:
     assert "state=st8" in url
 
 
+def test_post_form_returns_parsed_body() -> None:
+    resp = mock.MagicMock()
+    resp.status_code = 200
+    resp.content = b'{"access_token": "tok"}'
+
+    with mock.patch.object(requests, "post", return_value=resp) as post:
+        data = codex._post_form({"grant_type": "refresh_token"})
+
+    assert data == {"access_token": "tok"}
+    assert post.call_args.kwargs["timeout"] == codex._TOKEN_TIMEOUT
+
+
 @pytest.mark.parametrize(
     ("value", "expected"),
     [

tests/test_compaction.py

@@ -7,6 +7,7 @@ from typing import TYPE_CHECKING, Any
 
 import pytest
 from litellm.exceptions import BadRequestError, ContextWindowExceededError, RateLimitError
+from openai.types.responses import ResponseOutputMessage, ResponseOutputText
 
 from strix.config import ContextSettings
 from strix.llm import compaction
@@ -146,17 +147,35 @@ def _patch_budget(monkeypatch: pytest.MonkeyPatch, *, keep_tokens: int, window:
     context.auto_compact = True
     settings = SimpleNamespace(
         context=context,
-        llm=SimpleNamespace(api_key=None, api_base=None, timeout=1),
+        llm=SimpleNamespace(api_key=None, api_base=None, timeout=1, extra_headers=None),
     )
     monkeypatch.setattr(compaction, "load_settings", lambda: settings)
 
 
-def _patch_summary(monkeypatch: pytest.MonkeyPatch, text: str) -> None:
-    async def fake_acompletion(**_kwargs: Any) -> Any:
-        message = SimpleNamespace(content=text)
-        return SimpleNamespace(choices=[SimpleNamespace(message=message)])
+def _model_response(text: str) -> Any:
+    chunk = ResponseOutputText(annotations=[], text=text, type="output_text")
+    message = ResponseOutputMessage(
+        id="msg", content=[chunk], role="assistant", status="completed", type="message"
+    )
+    return SimpleNamespace(output=[message])
 
-    monkeypatch.setattr("strix.llm.compaction.litellm.acompletion", fake_acompletion)
+
+def _patch_summary(
+    monkeypatch: pytest.MonkeyPatch, text: str, captured: dict[str, Any] | None = None
+) -> None:
+    class FakeModel:
+        async def get_response(self, **kwargs: Any) -> Any:
+            if captured is not None:
+                captured.update(kwargs)
+            return _model_response(text)
+
+    class FakeProvider:
+        def get_model(self, model_name: str | None) -> Any:
+            if captured is not None:
+                captured["model"] = model_name
+            return FakeModel()
+
+    monkeypatch.setattr(compaction, "StrixProvider", FakeProvider)
 
 
 @pytest.mark.asyncio
@@ -189,19 +208,38 @@ async def test_maybe_compact_rewrites_and_keeps_pairs(monkeypatch: pytest.Monkey
 async def test_maybe_compact_updates_previous_summary(monkeypatch: pytest.MonkeyPatch) -> None:
     # Window large enough to leave real room for the summary instructions.
     _patch_budget(monkeypatch, keep_tokens=30, window=4_000)
-    captured: dict[str, str] = {}
-
-    async def fake_acompletion(**kwargs: Any) -> Any:
-        captured["prompt"] = kwargs["messages"][0]["content"]
-        return SimpleNamespace(choices=[SimpleNamespace(message=SimpleNamespace(content="NEW"))])
-
-    monkeypatch.setattr("strix.llm.compaction.litellm.acompletion", fake_acompletion)
+    captured: dict[str, Any] = {}
+    _patch_summary(monkeypatch, "NEW", captured)
 
     prior = compaction._checkpoint_item("OLD SUMMARY TEXT")
     session = FakeSession([prior, *_turns(12)])
 
     assert await compaction.maybe_compact(session, model="m", force=True) is True
-    assert "OLD SUMMARY TEXT" in captured["prompt"]
+    assert "OLD SUMMARY TEXT" in captured["input"]
+
+
+@pytest.mark.asyncio
+async def test_summarize_routes_through_provider_with_settings(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    _patch_budget(monkeypatch, keep_tokens=30, window=4_000)
+    monkeypatch.setattr(
+        compaction,
+        "load_settings",
+        lambda: SimpleNamespace(
+            llm=SimpleNamespace(
+                api_key=None, api_base=None, timeout=1, extra_headers={"X-Feature-Key": "svc"}
+            )
+        ),
+    )
+    captured: dict[str, Any] = {}
+    _patch_summary(monkeypatch, "S", captured)
+
+    assert await compaction._summarize("litellm/openai/some-model", "p", 64) == "S"
+    assert captured["model"] == "litellm/openai/some-model"
+    settings = captured["model_settings"]
+    assert settings.extra_headers == {"X-Feature-Key": "svc"}
+    assert settings.max_tokens == 64
 
 
 def test_fit_to_tokens_truncates_oversized_text(monkeypatch: pytest.MonkeyPatch) -> None:
@@ -233,19 +271,14 @@ def test_summary_output_tokens_capped_at_model_limit(monkeypatch: pytest.MonkeyP
 async def test_maybe_compact_bounds_summary_prompt(monkeypatch: pytest.MonkeyPatch) -> None:
     # A tiny window with a huge head must not send an oversized summary request.
     _patch_budget(monkeypatch, keep_tokens=30, window=4_000)
-    captured: dict[str, str] = {}
-
-    async def fake_acompletion(**kwargs: Any) -> Any:
-        captured["prompt"] = kwargs["messages"][0]["content"]
-        return SimpleNamespace(choices=[SimpleNamespace(message=SimpleNamespace(content="S"))])
-
-    monkeypatch.setattr("strix.llm.compaction.litellm.acompletion", fake_acompletion)
+    captured: dict[str, Any] = {}
+    _patch_summary(monkeypatch, "S", captured)
     big_turns = [{"role": "user", "content": "y" * 2_000} for _ in range(50)]
     session = FakeSession(big_turns)
 
     assert await compaction.maybe_compact(session, model="m") is True
     # count_tokens==len(chars); prompt must fit the model window.
-    assert len(captured["prompt"]) <= 4_000
+    assert len(captured["input"]) <= 4_000
 
 
 @pytest.mark.asyncio
@@ -256,27 +289,27 @@ async def test_summary_request_fits_when_room_is_below_old_floor(
     instructions = len(compaction._SUMMARY_INSTRUCTIONS)
     window = instructions + 64 + 256 + 300  # summary_max(64)+slack(256)+room(300)
     _patch_budget(monkeypatch, keep_tokens=30, window=window)
-    captured: dict[str, str] = {}
-
-    async def fake_acompletion(**kwargs: Any) -> Any:
-        captured["prompt"] = kwargs["messages"][0]["content"]
-        return SimpleNamespace(choices=[SimpleNamespace(message=SimpleNamespace(content="S"))])
-
-    monkeypatch.setattr("strix.llm.compaction.litellm.acompletion", fake_acompletion)
+    captured: dict[str, Any] = {}
+    _patch_summary(monkeypatch, "S", captured)
     session = FakeSession([{"role": "user", "content": "y" * 5_000} for _ in range(20)])
 
     assert await compaction.maybe_compact(session, model="m") is True
-    assert len(captured["prompt"]) <= window
+    assert len(captured["input"]) <= window
 
 
 @pytest.mark.asyncio
 async def test_maybe_compact_skips_when_summary_fails(monkeypatch: pytest.MonkeyPatch) -> None:
     _patch_budget(monkeypatch, keep_tokens=30, window=4_000)
 
-    async def fake_acompletion(**_kwargs: Any) -> Any:
-        raise RuntimeError("boom")
+    class BoomModel:
+        async def get_response(self, **_kwargs: Any) -> Any:
+            raise RuntimeError("boom")
 
-    monkeypatch.setattr("strix.llm.compaction.litellm.acompletion", fake_acompletion)
+    class BoomProvider:
+        def get_model(self, _model_name: str | None) -> Any:
+            return BoomModel()
+
+    monkeypatch.setattr(compaction, "StrixProvider", BoomProvider)
     session = FakeSession(_turns(12))
     before = await session.get_items()
 
@@ -290,17 +323,11 @@ async def test_maybe_compact_skips_when_no_room_to_summarise(
 ) -> None:
     # No room for any head -> no (doomed) summary is attempted.
     _patch_budget(monkeypatch, keep_tokens=30, window=200)
-    called = False
-
-    async def fake_acompletion(**_kwargs: Any) -> Any:
-        nonlocal called
-        called = True
-        return SimpleNamespace(choices=[SimpleNamespace(message=SimpleNamespace(content="S"))])
-
-    monkeypatch.setattr("strix.llm.compaction.litellm.acompletion", fake_acompletion)
+    captured: dict[str, Any] = {}
+    _patch_summary(monkeypatch, "S", captured)
     session = FakeSession(_turns(12))
     before = await session.get_items()
 
     assert await compaction.maybe_compact(session, model="m", force=True) is False
-    assert called is False
+    assert not captured
     assert await session.get_items() == before

tests/test_context_budget.py

@@ -21,6 +21,24 @@ def test_context_window_strips_provider_prefix() -> None:
     assert context_budget.context_window("openai/gpt-4o") == 128_000
 
 
+def test_context_window_chatgpt_prefix_skips_provider_auth(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    context_budget._model_info.cache_clear()
+    calls: list[str] = []
+
+    def _model_info(model: str) -> dict[str, int]:
+        calls.append(model)
+        return {"max_input_tokens": 1_050_000, "max_output_tokens": 128_000}
+
+    monkeypatch.setattr("strix.llm.context_budget.litellm.get_model_info", _model_info)
+    try:
+        assert context_budget.context_window("chatgpt/gpt-5.6-luna") == 1_050_000
+        assert calls == ["gpt-5.6-luna"]
+    finally:
+        context_budget._model_info.cache_clear()
+
+
 def test_context_window_unmapped_uses_fallback(monkeypatch: pytest.MonkeyPatch) -> None:
     context_budget._model_info.cache_clear()
 

tests/test_cost_tracking.py

@@ -7,9 +7,25 @@ from unittest.mock import MagicMock, patch
 
 import litellm
 import pytest
+from litellm.types.utils import LlmProviders
+from litellm.utils import ProviderConfigManager
 
-from strix.config.models import _configure_litellm_compatibility
-from strix.report.state import litellm_cost_callback
+from strix.config.models import (
+    _configure_litellm_compatibility,
+    _install_openrouter_stream_cost_capture,
+)
+from strix.report.state import (
+    ReportState,
+    litellm_cost_callback,
+    openrouter_stream_cost,
+    set_global_report_state,
+    streamed_openrouter_costs,
+)
+
+
+@pytest.fixture(autouse=True)
+def _clear_streamed_costs() -> None:
+    streamed_openrouter_costs.clear()
 
 
 def test_streaming_logging_stays_enabled_for_cost_callback() -> None:
@@ -151,3 +167,90 @@ def test_cost_callback_records_nothing_when_no_cost_available() -> None:
         litellm_cost_callback({"response_cost": None, "model": "x/y"}, response)
 
     report_state.record_observed_llm_cost.assert_not_called()
+
+
+def test_openrouter_stream_cost_extracts_plain_and_byok_totals() -> None:
+    assert openrouter_stream_cost({"cost": 0.003168}) == pytest.approx(0.003168)
+    assert openrouter_stream_cost(
+        {"cost": 0.01, "is_byok": True, "cost_details": {"upstream_inference_cost": 0.2}}
+    ) == pytest.approx(0.21)
+    # Upstream cost is only added for BYOK responses.
+    assert openrouter_stream_cost(
+        {"cost": 0.05, "is_byok": False, "cost_details": {"upstream_inference_cost": 0.04}}
+    ) == pytest.approx(0.05)
+    assert openrouter_stream_cost({"prompt_tokens": 10}) is None
+    assert openrouter_stream_cost(None) is None
+
+
+def test_cost_callback_recovers_streamed_openrouter_cost_by_response_id() -> None:
+    report_state = MagicMock()
+    streamed_openrouter_costs.remember("gen-abc", {"cost": 0.42})
+    # LiteLLM strips cost from the rebuilt streamed usage; only the id survives.
+    response = SimpleNamespace(id="gen-abc", usage=SimpleNamespace(cost=None), _hidden_params={})
+
+    with (
+        patch("strix.report.state.get_global_report_state", return_value=report_state),
+        patch("litellm.completion_cost", side_effect=ValueError("unknown model")),
+    ):
+        litellm_cost_callback({"response_cost": None, "model": "moonshotai/kimi-k3"}, response)
+
+    report_state.record_observed_llm_cost.assert_called_once_with(0.42)
+    # The entry is consumed so a later response cannot double-count it.
+    assert streamed_openrouter_costs.take(response) is None
+
+
+def test_streamed_openrouter_cost_prefers_provider_report_over_estimate() -> None:
+    report_state = MagicMock()
+    streamed_openrouter_costs.remember("gen-xyz", {"cost": 0.9})
+    response = SimpleNamespace(
+        id="gen-xyz",
+        usage=SimpleNamespace(prompt_tokens=10, completion_tokens=5, total_tokens=15),
+        _hidden_params={},
+    )
+
+    with (
+        patch("strix.report.state.get_global_report_state", return_value=report_state),
+        patch("litellm.completion_cost", return_value=0.1) as estimate,
+    ):
+        litellm_cost_callback({"response_cost": None, "model": "moonshotai/kimi-k3"}, response)
+
+    report_state.record_observed_llm_cost.assert_called_once_with(0.9)
+    estimate.assert_not_called()
+
+
+def test_streamed_openrouter_costs_ignores_entries_without_cost() -> None:
+    streamed_openrouter_costs.remember("gen-none", {"prompt_tokens": 10})
+    streamed_openrouter_costs.remember("", {"cost": 0.5})
+    assert streamed_openrouter_costs.take(SimpleNamespace(id="gen-none")) is None
+
+
+def test_streamed_openrouter_costs_cleared_on_new_run() -> None:
+    streamed_openrouter_costs.remember("gen-stale", {"cost": 0.7})
+    set_global_report_state(ReportState.__new__(ReportState))
+    assert streamed_openrouter_costs.take(SimpleNamespace(id="gen-stale")) is None
+
+
+def test_openrouter_stream_handler_records_cost() -> None:
+    _install_openrouter_stream_cost_capture()
+    # Resolve the config the way LiteLLM does in production so we prove the
+    # override is actually reachable through provider resolution, not just as a
+    # directly-constructed class.
+    config = ProviderConfigManager.get_provider_chat_config(
+        model="moonshotai/kimi-k3", provider=LlmProviders.OPENROUTER
+    )
+    assert config is not None
+    assert type(config).__name__ == "_StrixOpenrouterConfig"
+    handler = config.get_model_response_iterator(streaming_response=iter([]), sync_stream=True)
+
+    chunk = {
+        "id": "gen-stream",
+        "created": 1,
+        "model": "moonshotai/kimi-k3",
+        "choices": [{"index": 0, "delta": {"content": None}}],
+        "usage": {"prompt_tokens": 89, "completion_tokens": 138, "cost": 0.0035055},
+    }
+    handler.chunk_parser(chunk)
+
+    assert streamed_openrouter_costs.take(SimpleNamespace(id="gen-stream")) == pytest.approx(
+        0.0035055
+    )

tests/test_dedupe_model.py

@@ -44,6 +44,38 @@ def test_dedupe_endpoint_sent_per_call() -> None:
     assert (settings.extra_args or {})["api_key"] == "dedupe-key"
 
 
+def test_dedicated_dedupe_model_uses_own_headers_not_main() -> None:
+    dedupe = DedupeSettings(
+        STRIX_DEDUPE_MODEL="deepseek/cheap",
+        DEDUPE_LLM_EXTRA_HEADERS={"X-Dedupe": "yes"},
+    )
+    settings = _dedupe_model_settings(dedupe, "deepseek/cheap", 300)
+    assert settings.extra_headers == {"X-Dedupe": "yes"}
+
+
+def test_dedicated_dedupe_model_gets_no_main_headers_by_default(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    monkeypatch.setenv("LLM_EXTRA_HEADERS", json.dumps({"X-Main": "secret"}))
+    loader._cached = None
+    try:
+        dedupe = DedupeSettings(STRIX_DEDUPE_MODEL="deepseek/cheap")
+        settings = _dedupe_model_settings(dedupe, "deepseek/cheap", 300)
+        assert settings.extra_headers is None
+    finally:
+        loader._cached = None
+
+
+def test_fallback_dedupe_inherits_main_headers(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("LLM_EXTRA_HEADERS", json.dumps({"X-Main": "svc"}))
+    loader._cached = None
+    try:
+        settings = _dedupe_model_settings(DedupeSettings(), "openai/main-model", 300)
+        assert settings.extra_headers == {"X-Main": "svc"}
+    finally:
+        loader._cached = None
+
+
 def test_dedupe_defaults_are_empty() -> None:
     settings = DedupeSettings()
     assert settings.model is None

tests/test_disable_streaming.py

@@ -0,0 +1,326 @@
+"""Tests for LLM_DISABLE_STREAMING: serve the streamed run loop without SSE.
+
+A gateway that rejects ``stream:true`` (or delivers SSE unreliably) breaks the
+SDK run loop, which only issues streamed requests. ``_NonStreamingModel`` wraps
+the resolved model so each turn makes one non-streaming ``get_response`` and
+replays the completed result as a single terminal stream event. A local server
+that rejects streamed requests but answers non-streamed ones — including a
+structured tool call — proves the wrapper works where the stock model fails.
+"""
+
+from __future__ import annotations
+
+import json
+import threading
+from http.server import BaseHTTPRequestHandler, HTTPServer
+from typing import TYPE_CHECKING, Any
+
+import pytest
+from agents import Agent, Runner, function_tool
+from agents.model_settings import ModelSettings
+from agents.models.interface import Model, ModelProvider, ModelTracing
+from agents.models.openai_chatcompletions import OpenAIChatCompletionsModel
+from agents.run import RunConfig
+from openai import AsyncOpenAI, BadRequestError
+from openai.types.responses import (
+    ResponseCompletedEvent,
+    ResponseFunctionToolCall,
+    ResponseOutputMessage,
+    ResponseOutputText,
+)
+
+from strix.config import codex, loader
+from strix.config.loader import load_settings
+from strix.config.models import StrixProvider, _NonStreamingModel
+
+
+if TYPE_CHECKING:
+    from collections.abc import AsyncIterator, Iterator
+
+
+def _tool_call_completion() -> dict[str, Any]:
+    return {
+        "id": "chatcmpl-1",
+        "object": "chat.completion",
+        "created": 0,
+        "model": "gw-model",
+        "choices": [
+            {
+                "index": 0,
+                "finish_reason": "tool_calls",
+                "message": {
+                    "role": "assistant",
+                    "content": None,
+                    "tool_calls": [
+                        {
+                            "id": "call_1",
+                            "type": "function",
+                            "function": {"name": "do_thing", "arguments": '{"n": 1}'},
+                        }
+                    ],
+                },
+            }
+        ],
+        "usage": {"prompt_tokens": 5, "completion_tokens": 2, "total_tokens": 7},
+    }
+
+
+def _text_completion() -> dict[str, Any]:
+    return {
+        "id": "chatcmpl-2",
+        "object": "chat.completion",
+        "created": 0,
+        "model": "gw-model",
+        "choices": [
+            {
+                "index": 0,
+                "finish_reason": "stop",
+                "message": {"role": "assistant", "content": "hello from gateway"},
+            }
+        ],
+        "usage": {"prompt_tokens": 5, "completion_tokens": 3, "total_tokens": 8},
+    }
+
+
+_CAPTURED: dict[str, Any] = {}
+_PAYLOAD: dict[str, dict[str, Any]] = {"value": _tool_call_completion()}
+
+
+class _Handler(BaseHTTPRequestHandler):
+    """A gateway that only speaks non-streaming Chat Completions."""
+
+    def log_message(self, *args: Any) -> None:
+        pass
+
+    def do_POST(self) -> None:
+        length = int(self.headers.get("Content-Length", 0))
+        body = json.loads(self.rfile.read(length) or b"{}")
+        _CAPTURED.clear()
+        _CAPTURED.update(body)
+        if body.get("stream"):
+            payload = json.dumps(
+                {"error": {"message": "streaming is not supported by this endpoint"}}
+            ).encode()
+            self.send_response(400)
+            self.send_header("Content-Type", "application/json")
+            self.send_header("Content-Length", str(len(payload)))
+            self.end_headers()
+            self.wfile.write(payload)
+            return
+        payload = json.dumps(_PAYLOAD["value"]).encode()
+        self.send_response(200)
+        self.send_header("Content-Type", "application/json")
+        self.send_header("Content-Length", str(len(payload)))
+        self.end_headers()
+        self.wfile.write(payload)
+
+
+@pytest.fixture
+def gateway_url() -> Iterator[str]:
+    _PAYLOAD["value"] = _tool_call_completion()
+    server = HTTPServer(("127.0.0.1", 0), _Handler)
+    thread = threading.Thread(target=server.serve_forever, daemon=True)
+    thread.start()
+    try:
+        yield f"http://127.0.0.1:{server.server_address[1]}/v1"
+    finally:
+        server.shutdown()
+        server.server_close()
+
+
+def _model(base_url: str) -> OpenAIChatCompletionsModel:
+    client = AsyncOpenAI(api_key="tok", base_url=base_url)
+    return OpenAIChatCompletionsModel(model="gw-model", openai_client=client)
+
+
+def _call_kwargs() -> dict[str, Any]:
+    return {
+        "system_instructions": "s",
+        "input": "hi",
+        "model_settings": ModelSettings(),
+        "tools": [],
+        "output_schema": None,
+        "handoffs": [],
+        "tracing": ModelTracing.DISABLED,
+        "previous_response_id": None,
+        "conversation_id": None,
+        "prompt": None,
+    }
+
+
+async def _drain(gen: AsyncIterator[Any]) -> list[Any]:
+    return [event async for event in gen]
+
+
+@pytest.mark.asyncio
+async def test_stock_model_streaming_fails_on_non_streaming_gateway(gateway_url: str) -> None:
+    # The stock model issues stream:true and the gateway rejects it.
+    model = _model(gateway_url)
+    with pytest.raises(BadRequestError, match="streaming is not supported"):
+        await _drain(model.stream_response(**_call_kwargs()))
+    assert _CAPTURED["stream"] is True
+
+
+@pytest.mark.asyncio
+async def test_wrapper_streams_tool_call_without_streaming_request(gateway_url: str) -> None:
+    # The wrapper turns the streamed run-loop call into one non-streaming
+    # request and replays the completed result as a terminal stream event.
+    model = _NonStreamingModel(_model(gateway_url))
+    events = await _drain(model.stream_response(**_call_kwargs()))
+
+    assert _CAPTURED.get("stream") is not True
+    assert len(events) == 1
+    completed = events[0]
+    assert isinstance(completed, ResponseCompletedEvent)
+
+    tool_call = completed.response.output[0]
+    assert isinstance(tool_call, ResponseFunctionToolCall)
+    assert tool_call.name == "do_thing"
+    assert json.loads(tool_call.arguments) == {"n": 1}
+
+    assert completed.response.usage is not None
+    assert completed.response.usage.total_tokens == 7
+
+
+@pytest.mark.asyncio
+async def test_wrapper_streams_plain_text(gateway_url: str) -> None:
+    _PAYLOAD["value"] = _text_completion()
+    model = _NonStreamingModel(_model(gateway_url))
+    events = await _drain(model.stream_response(**_call_kwargs()))
+
+    assert _CAPTURED.get("stream") is not True
+    message = events[0].response.output[0]
+    assert isinstance(message, ResponseOutputMessage)
+    text = message.content[0]
+    assert isinstance(text, ResponseOutputText)
+    assert text.text == "hello from gateway"
+
+
+@pytest.mark.asyncio
+async def test_wrapper_get_response_stays_non_streaming(gateway_url: str) -> None:
+    # The non-streaming path is a plain pass-through to the inner model.
+    model = _NonStreamingModel(_model(gateway_url))
+    response = await model.get_response(**_call_kwargs())
+    assert _CAPTURED.get("stream") is not True
+    tool_call = response.output[0]
+    assert isinstance(tool_call, ResponseFunctionToolCall)
+    assert tool_call.name == "do_thing"
+
+
+_TURN_STREAM_FLAGS: list[bool] = []
+
+
+class _MultiTurnHandler(BaseHTTPRequestHandler):
+    """Non-streaming gateway: a tool call on turn 1, a final answer on turn 2."""
+
+    def log_message(self, *args: Any) -> None:
+        pass
+
+    def do_POST(self) -> None:
+        length = int(self.headers.get("Content-Length", 0))
+        body = json.loads(self.rfile.read(length) or b"{}")
+        _TURN_STREAM_FLAGS.append(bool(body.get("stream")))
+        completion = _tool_call_completion() if len(_TURN_STREAM_FLAGS) == 1 else _text_completion()
+        if len(_TURN_STREAM_FLAGS) > 1:
+            completion["choices"][0]["message"]["content"] = "all done"
+        payload = json.dumps(completion).encode()
+        self.send_response(200)
+        self.send_header("Content-Type", "application/json")
+        self.send_header("Content-Length", str(len(payload)))
+        self.end_headers()
+        self.wfile.write(payload)
+
+
+@pytest.fixture
+def multiturn_url() -> Iterator[str]:
+    _TURN_STREAM_FLAGS.clear()
+    server = HTTPServer(("127.0.0.1", 0), _MultiTurnHandler)
+    thread = threading.Thread(target=server.serve_forever, daemon=True)
+    thread.start()
+    try:
+        yield f"http://127.0.0.1:{server.server_address[1]}/v1"
+    finally:
+        server.shutdown()
+        server.server_close()
+
+
+@pytest.mark.asyncio
+async def test_run_loop_executes_tool_and_completes_without_streaming(multiturn_url: str) -> None:
+    # The whole streamed agent loop runs against a non-streaming gateway: the
+    # synthetic terminal event feeds the runner, which executes the tool and
+    # continues the turn until a final answer.
+    calls: list[int] = []
+
+    @function_tool
+    def do_thing(n: int) -> str:
+        calls.append(n)
+        return f"did {n}"
+
+    class _Provider(ModelProvider):
+        def get_model(self, model_name: str | None) -> Model:  # noqa: ARG002
+            return _NonStreamingModel(_model(multiturn_url))
+
+    agent = Agent(name="t", instructions="use the tool", tools=[do_thing], model="gw-model")
+    result = Runner.run_streamed(
+        agent, input="please", run_config=RunConfig(model_provider=_Provider())
+    )
+    async for _ in result.stream_events():
+        pass
+
+    assert calls == [1]  # tool executed with the streamed tool-call args
+    assert result.final_output == "all done"
+    assert len(_TURN_STREAM_FLAGS) == 2  # two turns, both...
+    assert not any(_TURN_STREAM_FLAGS)  # ...issued as non-streaming requests
+
+
+class _DummyModel(Model):
+    async def get_response(self, *args: Any, **kwargs: Any) -> Any:
+        raise NotImplementedError
+
+    def stream_response(self, *args: Any, **kwargs: Any) -> Any:
+        raise NotImplementedError
+
+
+@pytest.fixture
+def _reset_settings(monkeypatch: pytest.MonkeyPatch) -> Iterator[None]:
+    for key in ("STRIX_LLM", "LLM_DISABLE_STREAMING"):
+        monkeypatch.delenv(key, raising=False)
+    monkeypatch.setattr(loader, "_cached", None)
+    monkeypatch.setattr(loader, "_override", None)
+    yield
+
+
+def test_get_model_wraps_when_disabled(
+    monkeypatch: pytest.MonkeyPatch, _reset_settings: None
+) -> None:
+    inner = _DummyModel()
+    monkeypatch.setattr("strix.config.models.MultiProvider.get_model", lambda *_: inner)
+    monkeypatch.setenv("LLM_DISABLE_STREAMING", "true")
+    load_settings()
+
+    model = StrixProvider().get_model("openai/gpt-4o-mini")
+    assert isinstance(model, _NonStreamingModel)
+
+
+def test_get_model_unwrapped_by_default(
+    monkeypatch: pytest.MonkeyPatch, _reset_settings: None
+) -> None:
+    inner = _DummyModel()
+    monkeypatch.setattr("strix.config.models.MultiProvider.get_model", lambda *_: inner)
+    load_settings()
+
+    model = StrixProvider().get_model("openai/gpt-4o-mini")
+    assert model is inner
+
+
+def test_get_model_does_not_wrap_subscription_model(
+    monkeypatch: pytest.MonkeyPatch, _reset_settings: None
+) -> None:
+    # Subscription (ChatGPT) models are always streamed and must not be wrapped.
+    monkeypatch.setattr(codex, "subscription_model", lambda *_: "gpt-5.5")
+    monkeypatch.setattr(codex, "get_subscription_client", lambda: AsyncOpenAI(api_key="x"))
+    monkeypatch.setenv("LLM_DISABLE_STREAMING", "true")
+    load_settings()
+
+    model = StrixProvider().get_model("gpt-5.5")
+    assert not isinstance(model, _NonStreamingModel)

tests/test_e2e_budget_lifecycle.py

@@ -0,0 +1,372 @@
+from __future__ import annotations
+
+import asyncio
+from typing import TYPE_CHECKING, Any
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from strix.core import execution
+from strix.core.agents import AgentCoordinator, WaitKind
+from strix.core.execution import _start_child_runner, run_agent_loop
+from strix.core.hooks import BudgetExceededError, ReportUsageHooks
+from strix.core.sessions import open_agent_session
+
+
+if TYPE_CHECKING:
+    from collections.abc import AsyncIterator, Callable
+    from pathlib import Path
+
+
+MAX_BUDGET = 10.0
+COST_PER_CALL = 1.0
+
+
+class _FakeLedger:
+    def __init__(self) -> None:
+        self.cost = 0.0
+        self.calls: list[str] = []
+
+    def record_sdk_usage(self, **_kwargs: Any) -> None:
+        return
+
+    def get_total_llm_cost(self) -> float:
+        return self.cost
+
+
+class _FakeStream:
+    def __init__(
+        self,
+        *,
+        ledger: _FakeLedger,
+        hooks: ReportUsageHooks,
+        context: dict[str, Any],
+        agent: Any,
+        coordinator: AgentCoordinator,
+    ) -> None:
+        self._ledger = ledger
+        self._hooks = hooks
+        self._context = context
+        self._agent = agent
+        self._coordinator = coordinator
+        self.run_loop_exception: BaseException | None = None
+        self.final_output = None
+
+    async def stream_events(self) -> AsyncIterator[Any]:
+        agent_id = str(self._context.get("agent_id"))
+        self._ledger.cost += COST_PER_CALL
+        self._ledger.calls.append(agent_id)
+        ctx_wrapper = MagicMock()
+        ctx_wrapper.context = self._context
+        try:
+            await self._hooks.on_llm_end(ctx_wrapper, self._agent, MagicMock())
+        except Exception as exc:  # noqa: BLE001
+            self.run_loop_exception = exc
+        # Stand in for the explicit yield tool a real turn ends with. Without it
+        # every turn looks like a forgotten tool call and burns the recovery
+        # budget, which is a different scenario from the one under test here.
+        if self._coordinator.statuses.get(agent_id) == "running":
+            wait_kind: WaitKind = "user" if self._context.get("parent_id") is None else "agents"
+            await self._coordinator.park_waiting(agent_id, wait_kind=wait_kind)
+        items: tuple[Any, ...] = ()
+        for item in items:
+            yield item
+
+    def cancel(self, mode: str = "immediate") -> None:  # noqa: ARG002
+        return
+
+
+def _fake_runner(ledger: _FakeLedger, coordinator: AgentCoordinator) -> Any:
+    class _FakeRunner:
+        @staticmethod
+        def run_streamed(
+            agent: Any,
+            input: Any,  # noqa: A002, ARG004
+            *,
+            run_config: Any,  # noqa: ARG004
+            context: dict[str, Any],
+            max_turns: int,  # noqa: ARG004
+            session: Any,  # noqa: ARG004
+            hooks: ReportUsageHooks,
+        ) -> _FakeStream:
+            return _FakeStream(
+                ledger=ledger,
+                hooks=hooks,
+                context=context,
+                agent=agent,
+                coordinator=coordinator,
+            )
+
+    return _FakeRunner
+
+
+async def _noop_compact(*_args: Any, **_kwargs: Any) -> bool:
+    return False
+
+
+async def _wait_until(predicate: Callable[[], bool], *, timeout: float = 5.0) -> None:
+    async def _poll() -> None:
+        while not predicate():
+            await asyncio.sleep(0.01)
+
+    await asyncio.wait_for(_poll(), timeout=timeout)
+
+
+@pytest.mark.asyncio
+async def test_full_budget_lifecycle_reserve_then_cap(  # noqa: PLR0915
+    tmp_path: Path, monkeypatch: pytest.MonkeyPatch
+) -> None:
+    ledger = _FakeLedger()
+    hooks = ReportUsageHooks(model="test-model", max_budget_usd=MAX_BUDGET)
+    coordinator = AgentCoordinator()
+    monkeypatch.setattr(execution, "Runner", _fake_runner(ledger, coordinator))
+    monkeypatch.setattr(execution, "_compact_session", _noop_compact)
+
+    db_path = tmp_path / "agents.sqlite"
+    sessions: list[Any] = []
+    run_config = MagicMock()
+
+    await coordinator.register("root", "strix", parent_id=None)
+    root_session = open_agent_session("root", db_path)
+    sessions.append(root_session)
+
+    root_exc: list[BaseException] = []
+
+    async def _root_loop() -> None:
+        try:
+            await run_agent_loop(
+                agent=MagicMock(),
+                initial_input=[],
+                run_config=run_config,
+                context={"agent_id": "root", "parent_id": None},
+                max_turns=500,
+                coordinator=coordinator,
+                agent_id="root",
+                interactive=True,
+                session=root_session,
+                start_parked=True,
+                hooks=hooks,
+            )
+        except BaseException as exc:
+            root_exc.append(exc)
+            raise
+
+    with patch("strix.core.hooks.get_global_report_state", return_value=ledger):
+        root_task = asyncio.create_task(_root_loop())
+        await asyncio.sleep(0.05)
+
+        for child_id in ("child-a", "child-b"):
+            await coordinator.register(child_id, "recon", parent_id="root")
+            await _start_child_runner(
+                parent_ctx={"agent_id": "root", "parent_id": None},
+                coordinator=coordinator,
+                agents_db_path=db_path,
+                sessions_to_close=sessions,
+                run_config=run_config,
+                max_turns=500,
+                interactive=True,
+                child_agent=MagicMock(),
+                child_id=child_id,
+                name=f"recon-{child_id}",
+                parent_id="root",
+                task="probe things",
+                initial_input=[],
+                hooks=hooks,
+            )
+        await _wait_until(lambda: ledger.cost >= 2.0)
+        reserve_before = coordinator.reserve_stopped
+        assert reserve_before is False
+
+        async def _wait_spend_above(amount: float) -> None:
+            await _wait_until(lambda: ledger.cost > amount)
+
+        turn = 0
+        while ledger.cost < MAX_BUDGET * 0.90 - 1e-9:
+            target = ("child-a", "child-b")[turn % 2]
+            spent_before = ledger.cost
+            assert await coordinator.send(target, {"from": "user", "content": "keep going"})
+            await _wait_spend_above(spent_before)
+            turn += 1
+
+        await _wait_until(lambda: coordinator.reserve_stopped)
+
+        await _wait_until(
+            lambda: (
+                coordinator.statuses["child-a"] == "stopped"
+                and coordinator.statuses["child-b"] == "stopped"
+            )
+        )
+
+        assert coordinator.reserve_stopped is True
+
+        await _wait_until(lambda: coordinator.budget_stopped)
+        assert ledger.cost == pytest.approx(MAX_BUDGET)
+
+        assert len(ledger.calls) == 10
+        assert set(ledger.calls[:9]) == {"child-a", "child-b"}
+        assert ledger.calls[9] == "root"
+
+        root_items = await root_session.get_items()
+        notices = [item for item in root_items if "Budget reserve" in str(item)]
+        assert len(notices) == 1
+
+        with pytest.raises(BudgetExceededError):
+            await root_task
+        assert root_exc and isinstance(root_exc[0], BudgetExceededError)
+
+        assert {aid: str(status) for aid, status in coordinator.statuses.items()} == {
+            "root": "stopped",
+            "child-a": "stopped",
+            "child-b": "stopped",
+        }
+        assert coordinator.budget_stopped is True
+        assert coordinator.reserve_stopped is True
+
+    for session in sessions:
+        session.close()
+
+
+@pytest.mark.asyncio
+async def test_respawned_children_after_reserve_never_spend(
+    tmp_path: Path, monkeypatch: pytest.MonkeyPatch
+) -> None:
+    ledger = _FakeLedger()
+    ledger.cost = 9.5
+    hooks = ReportUsageHooks(model="test-model", max_budget_usd=MAX_BUDGET)
+    monkeypatch.setattr(execution, "_compact_session", _noop_compact)
+
+    coordinator = AgentCoordinator()
+    await coordinator.register("root", "strix", parent_id=None)
+    await coordinator.register("child-a", "recon", parent_id="root")
+    snap = await coordinator.snapshot()
+    snap["reserve_stopped"] = True
+
+    restored = AgentCoordinator()
+    await restored.restore(snap)
+    assert restored.reserve_stopped is True
+    monkeypatch.setattr(execution, "Runner", _fake_runner(ledger, restored))
+
+    sessions: list[Any] = []
+    with patch("strix.core.hooks.get_global_report_state", return_value=ledger):
+        await _start_child_runner(
+            parent_ctx={"agent_id": "root", "parent_id": None},
+            coordinator=restored,
+            agents_db_path=tmp_path / "agents.sqlite",
+            sessions_to_close=sessions,
+            run_config=MagicMock(),
+            max_turns=500,
+            interactive=True,
+            child_agent=MagicMock(),
+            child_id="child-a",
+            name="recon-child-a",
+            parent_id="root",
+            task="probe things",
+            initial_input=[],
+            hooks=hooks,
+        )
+        await _wait_until(lambda: restored.statuses["child-a"] == "stopped")
+
+    assert ledger.cost == pytest.approx(9.5)
+    assert ledger.calls == []
+    for session in sessions:
+        session.close()
+
+
+@pytest.mark.asyncio
+async def test_resumed_parked_root_after_reserve_is_renotified_and_finalizes(
+    tmp_path: Path, monkeypatch: pytest.MonkeyPatch
+) -> None:
+    ledger = _FakeLedger()
+    ledger.cost = 9.0
+    hooks = ReportUsageHooks(model="test-model", max_budget_usd=MAX_BUDGET)
+    monkeypatch.setattr(execution, "_compact_session", _noop_compact)
+
+    coordinator = AgentCoordinator()
+    await coordinator.register("root", "strix", parent_id=None)
+    await coordinator.set_status("root", "waiting")
+    snap = await coordinator.snapshot()
+    snap["reserve_stopped"] = True
+
+    restored = AgentCoordinator()
+    await restored.restore(snap)
+    assert restored.reserve_stopped is True
+    monkeypatch.setattr(execution, "Runner", _fake_runner(ledger, restored))
+
+    root_session = open_agent_session("root", tmp_path / "agents.sqlite")
+    with patch("strix.core.hooks.get_global_report_state", return_value=ledger):
+        root_task = asyncio.create_task(
+            run_agent_loop(
+                agent=MagicMock(),
+                initial_input=[],
+                run_config=MagicMock(),
+                context={"agent_id": "root", "parent_id": None},
+                max_turns=500,
+                coordinator=restored,
+                agent_id="root",
+                interactive=True,
+                session=root_session,
+                start_parked=True,
+                hooks=hooks,
+            )
+        )
+        with pytest.raises(BudgetExceededError):
+            await asyncio.wait_for(root_task, timeout=5.0)
+
+    assert ledger.calls == ["root"]
+    assert ledger.cost == pytest.approx(MAX_BUDGET)
+    root_items = await root_session.get_items()
+    notices = [item for item in root_items if "Budget reserve" in str(item)]
+    assert len(notices) == 1
+    root_session.close()
+
+
+@pytest.mark.asyncio
+async def test_interactive_budget_pause_then_user_message_extends_and_resumes(
+    tmp_path: Path, monkeypatch: pytest.MonkeyPatch
+) -> None:
+    ledger = _FakeLedger()
+    ledger.cost = 9.0
+    hooks = ReportUsageHooks(model="test-model", max_budget_usd=MAX_BUDGET, interactive=True)
+    coordinator = AgentCoordinator()
+    monkeypatch.setattr(execution, "Runner", _fake_runner(ledger, coordinator))
+    monkeypatch.setattr(execution, "_compact_session", _noop_compact)
+
+    coordinator.set_budget_extender(hooks.extend_budget)
+    await coordinator.register("root", "strix", parent_id=None)
+    root_session = open_agent_session("root", tmp_path / "agents.sqlite")
+
+    with patch("strix.core.hooks.get_global_report_state", return_value=ledger):
+        root_task = asyncio.create_task(
+            run_agent_loop(
+                agent=MagicMock(),
+                initial_input=[],
+                run_config=MagicMock(),
+                context={"agent_id": "root", "parent_id": None},
+                max_turns=500,
+                coordinator=coordinator,
+                agent_id="root",
+                interactive=True,
+                session=root_session,
+                start_parked=True,
+                hooks=hooks,
+            )
+        )
+        await asyncio.sleep(0.05)
+
+        assert await coordinator.send("root", {"from": "user", "content": "go"})
+        await _wait_until(lambda: coordinator.budget_paused)
+        assert coordinator.statuses["root"] == "budget_paused"
+        assert ledger.cost == pytest.approx(MAX_BUDGET)
+        assert not root_task.done()
+        assert coordinator.budget_stopped is False
+
+        assert await coordinator.send("root", {"from": "user", "content": "keep going"})
+        await _wait_until(lambda: not coordinator.budget_paused)
+        await _wait_until(lambda: ledger.cost > MAX_BUDGET)
+        await _wait_until(lambda: coordinator.statuses["root"] == "waiting")
+        assert not root_task.done()
+
+        root_task.cancel()
+        await root_task
+
+    root_session.close()

tests/test_execution_transient_retry.py

@@ -0,0 +1,174 @@
+from __future__ import annotations
+
+from typing import Any, cast
+
+import httpx
+import pytest
+from agents import RunConfig, Runner
+from openai import (
+    APIConnectionError,
+    APIError,
+    APIStatusError,
+    APITimeoutError,
+    BadRequestError,
+    InternalServerError,
+    RateLimitError,
+)
+
+from strix.config import codex
+from strix.core import execution
+from strix.core.agents import AgentCoordinator
+
+
+def _request() -> httpx.Request:
+    return httpx.Request("POST", "https://api.openai.com/v1/responses")
+
+
+def _midstream_api_error() -> APIError:
+    return APIError("An error occurred while processing the request.", _request(), body=None)
+
+
+def _status_error(status: int) -> APIStatusError:
+    return APIStatusError(
+        f"status {status}",
+        response=httpx.Response(status_code=status, request=_request()),
+        body=None,
+    )
+
+
+def test_midstream_api_error_is_transient() -> None:
+    assert execution._is_transient_model_error(_midstream_api_error()) is True
+
+
+def test_network_errors_are_transient() -> None:
+    assert execution._is_transient_model_error(APITimeoutError(_request())) is True
+    assert execution._is_transient_model_error(APIConnectionError(request=_request())) is True
+
+
+def test_server_errors_are_transient() -> None:
+    assert (
+        execution._is_transient_model_error(
+            InternalServerError("boom", response=httpx.Response(500, request=_request()), body=None)
+        )
+        is True
+    )
+    for status in (502, 503, 504, 408):
+        assert execution._is_transient_model_error(_status_error(status)) is True
+
+
+def test_rate_limit_is_retried() -> None:
+    rate_limited = RateLimitError(
+        "slow down", response=httpx.Response(429, request=_request()), body=None
+    )
+    assert execution._is_transient_model_error(rate_limited) is True
+
+
+def test_dns_and_connection_errors_are_transient() -> None:
+    assert execution._is_transient_model_error(OSError("nodename nor servname provided")) is True
+    assert execution._is_transient_model_error(ConnectionError("reset")) is True
+    assert execution._is_transient_model_error(TimeoutError("timed out")) is True
+
+
+def test_content_guardrail_is_not_retried() -> None:
+    guardrail = APIError(
+        "This content was flagged for possible cybersecurity risk",
+        _request(),
+        body=None,
+    )
+    assert codex.is_content_guardrail_error(guardrail) is True
+    assert execution._is_transient_model_error(guardrail) is False
+
+
+def test_client_errors_are_not_transient() -> None:
+    bad_request = BadRequestError(
+        "bad", response=httpx.Response(400, request=_request()), body=None
+    )
+    assert execution._is_transient_model_error(bad_request) is False
+    assert execution._is_transient_model_error(_status_error(404)) is False
+    assert execution._is_transient_model_error(ValueError("nope")) is False
+
+
+class _FakeStream:
+    def __init__(self, exc: BaseException | None = None) -> None:
+        self._exc = exc
+        self._events: list[Any] = []
+        self.run_loop_exception: BaseException | None = None
+
+    async def stream_events(self) -> Any:
+        if self._exc is not None:
+            raise self._exc
+        for event in self._events:
+            yield event
+
+
+def _patch_fast_backoff(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setattr(execution, "_TRANSIENT_MODEL_RETRY_BASE_DELAY_S", 0.0)
+    monkeypatch.setattr(execution, "_TRANSIENT_MODEL_RETRY_MAX_DELAY_S", 0.0)
+
+
+async def _run_once(
+    monkeypatch: pytest.MonkeyPatch,
+    streams: list[_FakeStream],
+) -> Any:
+    _patch_fast_backoff(monkeypatch)
+    calls = {"n": 0}
+
+    def _fake_run_streamed(*_args: Any, **_kwargs: Any) -> _FakeStream:
+        stream = streams[calls["n"]]
+        calls["n"] += 1
+        return stream
+
+    monkeypatch.setattr(Runner, "run_streamed", _fake_run_streamed)
+
+    coordinator = AgentCoordinator()
+    await coordinator.register("root", "strix", parent_id=None)
+
+    result = await execution._run_cycle(
+        object(),
+        coordinator,
+        "root",
+        input_data="task",
+        run_config=cast("RunConfig", object()),
+        context={},
+        max_turns=5,
+        session=None,
+        interactive=False,
+        event_sink=None,
+        hooks=None,
+    )
+    return result, calls["n"], coordinator
+
+
+@pytest.mark.asyncio
+async def test_run_cycle_retries_transient_midstream_error(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    streams = [_FakeStream(exc=_midstream_api_error()), _FakeStream()]
+    result, attempts, _coordinator = await _run_once(monkeypatch, streams)
+
+    assert result is streams[1]
+    assert attempts == 2
+
+
+@pytest.mark.asyncio
+async def test_run_cycle_gives_up_after_max_retries(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    streams = [
+        _FakeStream(exc=_midstream_api_error())
+        for _ in range(execution._MAX_TRANSIENT_MODEL_RETRIES + 1)
+    ]
+    with pytest.raises(APIError):
+        await _run_once(monkeypatch, streams)
+
+
+@pytest.mark.asyncio
+async def test_run_cycle_does_not_retry_permanent_error(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    bad_request = BadRequestError(
+        "bad", response=httpx.Response(400, request=_request()), body=None
+    )
+    streams = [_FakeStream(exc=bad_request), _FakeStream()]
+    with pytest.raises(BadRequestError):
+        await _run_once(monkeypatch, streams)

tests/test_hooks.py

@@ -2,11 +2,18 @@
 
 from __future__ import annotations
 
+from typing import Any
 from unittest.mock import MagicMock, patch
 
 import pytest
 
-from strix.core.hooks import BudgetExceededError, ReportUsageHooks
+from strix.core.hooks import (
+    BudgetExceededError,
+    BudgetPausedError,
+    ReportUsageHooks,
+    SubagentBudgetReservedError,
+    recomputed_budget_flags,
+)
 
 
 def _make_hooks(max_budget: float | None) -> ReportUsageHooks:
@@ -20,9 +27,22 @@ def _make_report_state(cost: float) -> MagicMock:
     return state
 
 
-def _make_context(agent_id: str = "test-agent") -> MagicMock:
+def _make_context(agent_id: str = "test-agent", parent_id: str | None = None) -> MagicMock:
     ctx: MagicMock = MagicMock()
-    ctx.context = {"agent_id": agent_id}
+    ctx.context = {"agent_id": agent_id, "parent_id": parent_id}
+    return ctx
+
+
+def _make_warn_context(
+    *,
+    requests: int,
+    parent_id: str | None = None,
+    agent_id: str = "test-agent",
+) -> MagicMock:
+    ctx: MagicMock = MagicMock()
+    ctx.context = {"agent_id": agent_id, "parent_id": parent_id}
+    ctx.usage = MagicMock()
+    ctx.usage.requests = requests
     return ctx
 
 
@@ -89,6 +109,127 @@ async def test_error_message_includes_amounts() -> None:
         assert "7.1234" in str(exc_info.value)
 
 
+@pytest.mark.asyncio
+async def test_subagent_stops_at_reserve() -> None:
+    hooks = _make_hooks(10.0)
+    state = _make_report_state(9.0)
+    with (
+        patch("strix.core.hooks.get_global_report_state", return_value=state),
+        pytest.raises(SubagentBudgetReservedError),
+    ):
+        await hooks.on_llm_end(_make_context(parent_id="root-1"), MagicMock(), MagicMock())
+
+
+@pytest.mark.asyncio
+async def test_subagent_below_reserve_does_not_raise() -> None:
+    hooks = _make_hooks(10.0)
+    state = _make_report_state(8.99)
+    with patch("strix.core.hooks.get_global_report_state", return_value=state):
+        await hooks.on_llm_end(_make_context(parent_id="root-1"), MagicMock(), MagicMock())
+
+
+@pytest.mark.asyncio
+async def test_subagent_overshoot_to_full_budget_triggers_scan_wide_stop() -> None:
+    hooks = _make_hooks(10.0)
+    state = _make_report_state(10.5)
+    with (
+        patch("strix.core.hooks.get_global_report_state", return_value=state),
+        pytest.raises(BudgetExceededError),
+    ):
+        await hooks.on_llm_end(_make_context(parent_id="root-1"), MagicMock(), MagicMock())
+
+
+@pytest.mark.asyncio
+async def test_root_keeps_running_inside_reserve() -> None:
+    hooks = _make_hooks(10.0)
+    state = _make_report_state(9.5)
+    with patch("strix.core.hooks.get_global_report_state", return_value=state):
+        await hooks.on_llm_end(_make_context(parent_id=None), MagicMock(), MagicMock())
+
+
+@pytest.mark.asyncio
+async def test_root_hard_stop_stays_at_full_budget() -> None:
+    hooks = _make_hooks(10.0)
+    state = _make_report_state(10.0)
+    with (
+        patch("strix.core.hooks.get_global_report_state", return_value=state),
+        pytest.raises(BudgetExceededError),
+    ):
+        await hooks.on_llm_end(_make_context(parent_id=None), MagicMock(), MagicMock())
+
+
+@pytest.mark.asyncio
+async def test_budget_warning_mentions_reserve() -> None:
+    hooks = ReportUsageHooks(model="test-model", max_budget_usd=10.0)
+    state = _make_report_state(7.5)
+    root_items: list[Any] = []
+    sub_items: list[Any] = []
+    with patch("strix.core.hooks.get_global_report_state", return_value=state):
+        await hooks.on_llm_start(
+            _make_warn_context(requests=0, parent_id=None), MagicMock(), None, root_items
+        )
+        await hooks.on_llm_start(
+            _make_warn_context(requests=0, parent_id="root-1"), MagicMock(), None, sub_items
+        )
+    assert "stopped at 90%" in root_items[0]["content"]
+    assert "stopped at 90%" in sub_items[0]["content"]
+    assert "root agent's final report" in sub_items[0]["content"]
+
+
+@pytest.mark.asyncio
+async def test_subagent_critical_budget_warning_reachable_before_reserve() -> None:
+    hooks = ReportUsageHooks(model="test-model", max_budget_usd=10.0)
+    state = _make_report_state(8.6)
+    sub_items: list[Any] = []
+    root_items: list[Any] = []
+    with patch("strix.core.hooks.get_global_report_state", return_value=state):
+        await hooks.on_llm_start(
+            _make_warn_context(requests=0, parent_id="root-1"), MagicMock(), None, sub_items
+        )
+        await hooks.on_llm_start(
+            _make_warn_context(requests=0, parent_id=None), MagicMock(), None, root_items
+        )
+    assert "[CRITICAL]" in sub_items[0]["content"]
+    assert "[URGENT]" in root_items[0]["content"]
+
+
+@pytest.mark.parametrize(
+    ("parent_id", "cost", "expected"),
+    [
+        ("root-1", 0.0, None),
+        ("root-1", 8.9999, None),
+        ("root-1", 9.0, SubagentBudgetReservedError),
+        ("root-1", 9.0001, SubagentBudgetReservedError),
+        ("root-1", 9.5, SubagentBudgetReservedError),
+        ("root-1", 9.9999, SubagentBudgetReservedError),
+        ("root-1", 10.0, BudgetExceededError),
+        ("root-1", 10.0001, BudgetExceededError),
+        ("root-1", 25.0, BudgetExceededError),
+        (None, 0.0, None),
+        (None, 8.9999, None),
+        (None, 9.0, None),
+        (None, 9.5, None),
+        (None, 9.9999, None),
+        (None, 10.0, BudgetExceededError),
+        (None, 10.0001, BudgetExceededError),
+        (None, 25.0, BudgetExceededError),
+    ],
+)
+@pytest.mark.asyncio
+async def test_budget_enforcement_decision_table(
+    parent_id: str | None, cost: float, expected: type[Exception] | None
+) -> None:
+    hooks = _make_hooks(10.0)
+    state = _make_report_state(cost)
+    with patch("strix.core.hooks.get_global_report_state", return_value=state):
+        if expected is None:
+            await hooks.on_llm_end(_make_context(parent_id=parent_id), MagicMock(), MagicMock())
+        else:
+            with pytest.raises(expected):
+                await hooks.on_llm_end(_make_context(parent_id=parent_id), MagicMock(), MagicMock())
+    state.record_sdk_usage.assert_called_once()
+
+
 @pytest.mark.asyncio
 async def test_no_raise_when_report_state_none() -> None:
     hooks = _make_hooks(1.0)
@@ -106,3 +247,247 @@ def test_non_positive_budget_rejected(bad_budget: float) -> None:
 def test_budget_exceeded_error_is_runtime_error() -> None:
     err = BudgetExceededError("test")
     assert isinstance(err, RuntimeError)
+
+
+def test_non_positive_max_turns_rejected() -> None:
+    with pytest.raises(ValueError, match="positive integer"):
+        ReportUsageHooks(model="test-model", max_turns=0)
+
+
+@pytest.mark.asyncio
+async def test_no_turn_warning_below_first_band() -> None:
+    hooks = ReportUsageHooks(model="test-model", max_turns=100)
+    items: list[Any] = []
+    await hooks.on_llm_start(_make_warn_context(requests=68), MagicMock(), None, items)
+    assert items == []
+
+
+@pytest.mark.asyncio
+async def test_turn_warning_notice_band() -> None:
+    hooks = ReportUsageHooks(model="test-model", max_turns=100)
+    items: list[Any] = []
+    await hooks.on_llm_start(_make_warn_context(requests=69), MagicMock(), None, items)
+    assert len(items) == 1
+    content = items[0]["content"]
+    assert "[NOTICE]" in content
+    assert "finish_scan" in content
+
+
+@pytest.mark.asyncio
+async def test_turn_warning_escalates_and_names_subagent_tool() -> None:
+    hooks = ReportUsageHooks(model="test-model", max_turns=100)
+    items: list[Any] = []
+    await hooks.on_llm_start(
+        _make_warn_context(requests=95, parent_id="root-1"), MagicMock(), None, items
+    )
+    assert len(items) == 1
+    content = items[0]["content"]
+    assert "[CRITICAL]" in content
+    assert "agent_finish" in content
+
+
+@pytest.mark.asyncio
+async def test_turn_warning_root_directive_distinct_from_subagent() -> None:
+    hooks = ReportUsageHooks(model="test-model", max_turns=100)
+
+    root_items: list[Any] = []
+    await hooks.on_llm_start(
+        _make_warn_context(requests=85, parent_id=None), MagicMock(), None, root_items
+    )
+    root = root_items[0]["content"]
+
+    sub_items: list[Any] = []
+    await hooks.on_llm_start(
+        _make_warn_context(requests=85, parent_id="root-1"), MagicMock(), None, sub_items
+    )
+    sub = sub_items[0]["content"]
+
+    assert root != sub
+    assert "root agent" in root
+    assert "finish_scan" in root
+    assert "agent_finish" not in root
+    assert "whole scan" in root
+    assert "sub-agent" in sub
+    assert "agent_finish" in sub
+    assert "finish_scan" not in sub
+    assert "confirmed" in sub
+
+
+@pytest.mark.asyncio
+async def test_budget_warning_root_directive_distinct_from_subagent() -> None:
+    hooks = ReportUsageHooks(model="test-model", max_budget_usd=10.0)
+    state = _make_report_state(8.6)
+
+    root_items: list[Any] = []
+    sub_items: list[Any] = []
+    with patch("strix.core.hooks.get_global_report_state", return_value=state):
+        await hooks.on_llm_start(
+            _make_warn_context(requests=0, parent_id=None), MagicMock(), None, root_items
+        )
+        await hooks.on_llm_start(
+            _make_warn_context(requests=0, parent_id="root-1"), MagicMock(), None, sub_items
+        )
+
+    root = root_items[0]["content"]
+    sub = sub_items[0]["content"]
+    assert "finish_scan" in root and "agent_finish" not in root
+    assert "agent_finish" in sub and "finish_scan" not in sub
+    assert "confirmed" in sub
+
+
+@pytest.mark.parametrize("parent_id", [None, "root-1"])
+@pytest.mark.asyncio
+async def test_turn_warning_directive_escalates_per_stage(parent_id: str | None) -> None:
+    hooks = ReportUsageHooks(model="test-model", max_turns=100)
+    contents: dict[str, str] = {}
+    for label, requests in (("notice", 69), ("urgent", 85), ("critical", 95)):
+        items: list[Any] = []
+        await hooks.on_llm_start(
+            _make_warn_context(requests=requests, parent_id=parent_id), MagicMock(), None, items
+        )
+        contents[label] = items[0]["content"]
+
+    assert len({contents["notice"], contents["urgent"], contents["critical"]}) == 3
+    assert "[NOTICE]" in contents["notice"] and "begin planning" in contents["notice"]
+    assert "[URGENT]" in contents["urgent"] and "prioritize" in contents["urgent"]
+    assert "[CRITICAL]" in contents["critical"] and "STOP" in contents["critical"]
+
+
+@pytest.mark.asyncio
+async def test_no_turn_warning_when_max_turns_unset() -> None:
+    hooks = ReportUsageHooks(model="test-model")
+    items: list[Any] = []
+    await hooks.on_llm_start(_make_warn_context(requests=999), MagicMock(), None, items)
+    assert items == []
+
+
+@pytest.mark.asyncio
+async def test_no_budget_warning_below_first_band() -> None:
+    hooks = ReportUsageHooks(model="test-model", max_budget_usd=10.0)
+    state = _make_report_state(6.9)
+    items: list[Any] = []
+    with patch("strix.core.hooks.get_global_report_state", return_value=state):
+        await hooks.on_llm_start(_make_warn_context(requests=0), MagicMock(), None, items)
+    assert items == []
+
+
+@pytest.mark.asyncio
+async def test_budget_warning_broadcast_content() -> None:
+    hooks = ReportUsageHooks(model="test-model", max_budget_usd=10.0)
+    state = _make_report_state(9.6)
+    items: list[Any] = []
+    with patch("strix.core.hooks.get_global_report_state", return_value=state):
+        await hooks.on_llm_start(_make_warn_context(requests=0), MagicMock(), None, items)
+    assert len(items) == 1
+    content = items[0]["content"]
+    assert "[CRITICAL]" in content
+    assert "shared across every agent" in content
+
+
+@pytest.mark.asyncio
+async def test_turn_and_budget_warnings_stack() -> None:
+    hooks = ReportUsageHooks(model="test-model", max_budget_usd=10.0, max_turns=100)
+    state = _make_report_state(8.6)
+    items: list[Any] = []
+    with patch("strix.core.hooks.get_global_report_state", return_value=state):
+        await hooks.on_llm_start(_make_warn_context(requests=89), MagicMock(), None, items)
+    assert len(items) == 2
+    joined = " ".join(i["content"] for i in items)
+    assert "Turn budget" in joined
+    assert "cost budget" in joined
+
+
+def _make_interactive_hooks(max_budget: float | None) -> ReportUsageHooks:
+    return ReportUsageHooks(model="test-model", max_budget_usd=max_budget, interactive=True)
+
+
+@pytest.mark.asyncio
+async def test_interactive_at_budget_pauses_instead_of_stopping() -> None:
+    hooks = _make_interactive_hooks(10.0)
+    state = _make_report_state(10.0)
+    with (
+        patch("strix.core.hooks.get_global_report_state", return_value=state),
+        pytest.raises(BudgetPausedError),
+    ):
+        await hooks.on_llm_end(_make_context(parent_id=None), MagicMock(), MagicMock())
+
+
+@pytest.mark.asyncio
+async def test_interactive_subagent_has_no_reserve() -> None:
+    hooks = _make_interactive_hooks(10.0)
+    state = _make_report_state(9.5)
+    with patch("strix.core.hooks.get_global_report_state", return_value=state):
+        await hooks.on_llm_end(_make_context(parent_id="root-1"), MagicMock(), MagicMock())
+
+
+@pytest.mark.asyncio
+async def test_interactive_subagent_pauses_at_full_budget() -> None:
+    hooks = _make_interactive_hooks(10.0)
+    state = _make_report_state(10.5)
+    with (
+        patch("strix.core.hooks.get_global_report_state", return_value=state),
+        pytest.raises(BudgetPausedError),
+    ):
+        await hooks.on_llm_end(_make_context(parent_id="root-1"), MagicMock(), MagicMock())
+
+
+@pytest.mark.asyncio
+async def test_extend_budget_lifts_the_pause() -> None:
+    hooks = _make_interactive_hooks(10.0)
+    state = _make_report_state(10.5)
+    hooks.extend_budget()
+    with patch("strix.core.hooks.get_global_report_state", return_value=state):
+        await hooks.on_llm_end(_make_context(parent_id=None), MagicMock(), MagicMock())
+
+
+@pytest.mark.asyncio
+async def test_extend_budget_adds_original_amount_each_time() -> None:
+    hooks = _make_interactive_hooks(10.0)
+    hooks.extend_budget()
+    hooks.extend_budget()
+    state = _make_report_state(29.9)
+    with patch("strix.core.hooks.get_global_report_state", return_value=state):
+        await hooks.on_llm_end(_make_context(parent_id=None), MagicMock(), MagicMock())
+    state = _make_report_state(30.0)
+    with (
+        patch("strix.core.hooks.get_global_report_state", return_value=state),
+        pytest.raises(BudgetPausedError),
+    ):
+        await hooks.on_llm_end(_make_context(parent_id=None), MagicMock(), MagicMock())
+
+
+@pytest.mark.asyncio
+async def test_interactive_subagent_uses_root_warning_bands() -> None:
+    hooks = _make_interactive_hooks(10.0)
+    state = _make_report_state(7.4)
+    items: list[Any] = []
+    with patch("strix.core.hooks.get_global_report_state", return_value=state):
+        await hooks.on_llm_start(
+            _make_warn_context(requests=0, parent_id="root-1"), MagicMock(), None, items
+        )
+    assert len(items) == 1
+    content = items[0]["content"]
+    assert "[NOTICE]" in content
+    assert "paused until the user chooses to continue" in content
+    assert "reserve" not in content.lower()
+
+
+@pytest.mark.parametrize(
+    ("cost", "max_budget", "interactive", "expected"),
+    [
+        (0.0, None, False, (False, False)),
+        (100.0, None, False, (False, False)),
+        (5.0, 10.0, False, (False, False)),
+        (9.0, 10.0, False, (False, True)),
+        (10.0, 10.0, False, (True, True)),
+        (10.0, 20.0, False, (False, False)),
+        (10.0, 10.0, True, (False, False)),
+    ],
+)
+def test_recomputed_budget_flags(
+    cost: float,
+    max_budget: float | None,
+    interactive: bool,
+    expected: tuple[bool, bool],
+) -> None:
+    assert recomputed_budget_flags(cost, max_budget, interactive=interactive) == expected

tests/test_inputs.py

@@ -5,6 +5,7 @@ from __future__ import annotations
 from itertools import pairwise
 from typing import Any
 
+import litellm
 import pytest
 
 from strix.core.inputs import build_root_task, child_initial_input, make_model_settings
@@ -55,6 +56,103 @@ def test_child_initial_input_no_consecutive_same_role(parent_history: list[Any])
     assert all(prev != nxt for prev, nxt in pairwise(roles))
 
 
+def _cache_points(model_name: str) -> Any:
+    extra = make_model_settings(None, model_name=model_name).extra_args or {}
+    return extra.get("cache_control_injection_points")
+
+
+def test_make_model_settings_enables_prompt_cache_for_bedrock_claude() -> None:
+    assert _cache_points("bedrock/global.anthropic.claude-opus-4-8") == [
+        {"location": "message", "role": "system"},
+        {"location": "tool_config"},
+        {"location": "message", "index": -1},
+    ]
+
+
+@pytest.mark.parametrize(
+    "model_name",
+    [
+        "anthropic/claude-sonnet-4-5",
+        "openrouter/anthropic/claude-3.5-sonnet",
+        "vertex_ai/claude-sonnet-4-5",
+    ],
+)
+def test_make_model_settings_enables_prompt_cache_for_non_bedrock_claude(model_name: str) -> None:
+    assert _cache_points(model_name) == [
+        {"location": "message", "role": "system"},
+        {"location": "message", "index": -1},
+    ]
+
+
+def test_tool_config_point_not_leaked_to_non_bedrock_claude() -> None:
+    # LiteLLM only consumes tool_config on Bedrock; elsewhere it leaks onto the
+    # wire and native Anthropic 400s.
+    for model in ("anthropic/claude-sonnet-4-5", "openrouter/anthropic/claude-3.5-sonnet"):
+        points = _cache_points(model) or []
+        assert all(p.get("location") != "tool_config" for p in points)
+
+
+def test_prompt_cache_can_be_disabled() -> None:
+    assert (
+        make_model_settings(
+            None, model_name="anthropic/claude-sonnet-4-5", prompt_cache=False
+        ).extra_args
+        is None
+    )
+
+
+@pytest.mark.parametrize("model_name", ["gpt-5", "vertex_ai/gemini-2.5-pro", "openai/o3"])
+def test_make_model_settings_no_prompt_cache_for_non_claude(model_name: str) -> None:
+    assert make_model_settings(None, model_name=model_name).extra_args is None
+
+
+def test_no_prompt_cache_for_unmapped_bedrock_claude_model(monkeypatch: Any) -> None:
+    # A Bedrock Claude model LiteLLM hasn't mapped must run uncached, not crash.
+    unmapped = "bedrock/global.anthropic.claude-brand-new-9"
+    monkeypatch.setattr(litellm, "model_cost", {}, raising=False)
+    if getattr(getattr(litellm, "utils", None), "supports_prompt_caching", None):
+        monkeypatch.setattr(litellm.utils, "supports_prompt_caching", lambda *_a, **_k: False)
+
+    assert make_model_settings(None, model_name=unmapped).extra_args is None
+
+
+def test_prompt_cache_kept_for_non_bedrock_claude_even_if_unmapped(monkeypatch: Any) -> None:
+    # Only Bedrock hard-rejects unknown cache fields, so only Bedrock is guarded.
+    monkeypatch.setattr(litellm, "model_cost", {}, raising=False)
+    if getattr(getattr(litellm, "utils", None), "supports_prompt_caching", None):
+        monkeypatch.setattr(litellm.utils, "supports_prompt_caching", lambda *_a, **_k: False)
+
+    for model in ("anthropic/claude-brand-new-9", "openrouter/anthropic/claude-brand-new"):
+        assert _cache_points(model) == [
+            {"location": "message", "role": "system"},
+            {"location": "message", "index": -1},
+        ]
+
+
+def test_conversation_tail_breakpoint_moves_with_appended_transcript() -> None:
+    # LiteLLM must place the index=-1 cache_control on the last message however
+    # long the transcript grows.
+    hook_mod = pytest.importorskip("litellm.integrations.anthropic_cache_control_hook")
+    apply = hook_mod.AnthropicCacheControlHook._apply_message_injections
+    points = _cache_points("bedrock/global.anthropic.claude-opus-4-8")
+    msg_points = [p for p in points if p.get("location") == "message"]
+
+    def last_msg_cache_control(n_turns: int) -> Any:
+        messages: list[dict[str, Any]] = [{"role": "system", "content": "stable prompt"}]
+        for i in range(n_turns):
+            messages.append({"role": "assistant", "content": f"turn {i} action"})
+            messages.append({"role": "user", "content": f"turn {i} tool result"})
+        processed = apply(msg_points, messages, 4)
+        last = processed[-1]
+        content = last.get("content")
+        if isinstance(content, list):
+            return content[-1].get("cache_control")
+        return last.get("cache_control")
+
+    assert last_msg_cache_control(2) == {"type": "ephemeral"}
+    assert last_msg_cache_control(20) == {"type": "ephemeral"}
+
+
 def test_build_root_task_empty_config() -> None:
     assert build_root_task({}) == ""
 
@@ -174,6 +272,30 @@ def test_make_model_settings_omits_timeout_when_unset() -> None:
     assert settings.extra_args is None
 
 
+def test_make_model_settings_sets_extra_headers() -> None:
+    settings = make_model_settings(
+        "none",
+        model_name="openai/some-model",
+        extra_headers={"X-Feature-Key": "svc", "X-Tenant": "acme"},
+    )
+
+    assert settings.extra_headers == {"X-Feature-Key": "svc", "X-Tenant": "acme"}
+
+
+def test_make_model_settings_omits_extra_headers_when_unset() -> None:
+    assert make_model_settings("none", model_name="gpt-4o").extra_headers is None
+
+
+def test_make_model_settings_extra_headers_survive_reasoning_resolve() -> None:
+    settings = make_model_settings(
+        "high",
+        model_name="openai/o3",
+        extra_headers={"X-Feature-Key": "svc"},
+    )
+
+    assert settings.extra_headers == {"X-Feature-Key": "svc"}
+
+
 def test_make_model_settings_timeout_survives_reasoning_resolve() -> None:
     # Reasoning is resolved via ModelSettings.resolve(); the timeout in extra_args
     # must not be dropped when a reasoning override is merged in.

tests/test_install_script.py

@@ -0,0 +1,154 @@
+from __future__ import annotations
+
+import stat
+import subprocess
+import sys
+import tarfile
+from pathlib import Path
+
+import pytest
+
+
+RELEASE_VERSION = "9.9.9"
+RELEASE_TARGET = "linux-arm64"
+
+pytestmark = pytest.mark.skipif(
+    sys.platform == "win32",
+    reason="scripts/install.sh is a POSIX shell installer",
+)
+
+
+def _write_executable(path: Path, content: str) -> None:
+    path.write_text(content, encoding="utf-8")
+    path.chmod(path.stat().st_mode | stat.S_IXUSR)
+
+
+def _create_release_archive(tmp_path: Path) -> Path:
+    binary_name = f"strix-{RELEASE_VERSION}-{RELEASE_TARGET}"
+    binary_path = tmp_path / binary_name
+    _write_executable(binary_path, f"#!/bin/sh\nprintf 'strix {RELEASE_VERSION}\\n'\n")
+
+    archive_path = tmp_path / f"{binary_name}.tar.gz"
+    with tarfile.open(archive_path, "w:gz") as archive:
+        archive.add(binary_path, arcname=binary_name)
+    return archive_path
+
+
+def _create_mock_commands(tmp_path: Path, machine: str) -> Path:
+    mock_bin = tmp_path / "mock-bin"
+    mock_bin.mkdir()
+    _write_executable(
+        mock_bin / "uname",
+        f"""#!/bin/sh
+case "$1" in
+  -s) echo Linux ;;
+  -m) echo {machine} ;;
+  *) echo "unexpected uname argument: $*" >&2; exit 1 ;;
+esac
+""",
+    )
+    _write_executable(mock_bin / "docker", "#!/bin/sh\nexit 0\n")
+    _write_executable(
+        mock_bin / "curl",
+        """#!/bin/sh
+output=""
+while [ "$#" -gt 0 ]; do
+  if [ "$1" = "-o" ]; then
+    output="$2"
+    shift 2
+    continue
+  fi
+  printf '%s\\n' "$1" >> "$STRIX_TEST_CURL_LOG"
+  shift
+done
+cp "$STRIX_TEST_ARCHIVE" "$output"
+""",
+    )
+    return mock_bin
+
+
+def _create_installer_environment(
+    tmp_path: Path,
+    archive_path: Path,
+    mock_bin: Path,
+) -> tuple[dict[str, str], Path, Path]:
+    """Build the installer environment explicitly.
+
+    Every variable the installer reads is listed here, so no inherited value
+    (`XDG_CONFIG_HOME`, `GITHUB_ACTIONS`, `TMPDIR`, ...) can send a write
+    outside the sandbox or change the code path under test.
+    """
+    home_path = tmp_path / "home"
+    home_path.mkdir()
+    download_path = tmp_path / "downloads"
+    download_path.mkdir()
+    curl_log_path = tmp_path / "curl.log"
+    environment = {
+        "HOME": str(home_path),
+        "XDG_CONFIG_HOME": str(home_path / ".config"),
+        "PATH": f"{mock_bin}:/usr/bin:/bin",
+        "SHELL": "/bin/bash",
+        "TMPDIR": str(download_path),
+        "STRIX_TEST_ARCHIVE": str(archive_path),
+        "STRIX_TEST_CURL_LOG": str(curl_log_path),
+        "VERSION": RELEASE_VERSION,
+    }
+    return environment, home_path, curl_log_path
+
+
+def _run_installer(
+    repository_root: Path,
+    environment: dict[str, str],
+) -> subprocess.CompletedProcess[str]:
+    return subprocess.run(  # noqa: S603
+        ["/bin/bash", str(repository_root / "scripts/install.sh")],
+        cwd=repository_root,
+        env=environment,
+        capture_output=True,
+        text=True,
+        check=False,
+    )
+
+
+def test_installer_downloads_and_runs_linux_arm64_release(tmp_path: Path) -> None:
+    repository_root = Path(__file__).resolve().parents[1]
+    archive_path = _create_release_archive(tmp_path)
+    mock_bin = _create_mock_commands(tmp_path, machine="aarch64")
+    environment, home_path, curl_log_path = _create_installer_environment(
+        tmp_path,
+        archive_path,
+        mock_bin,
+    )
+
+    result = _run_installer(repository_root, environment)
+
+    assert result.returncode == 0, result.stderr
+    expected_filename = f"strix-{RELEASE_VERSION}-{RELEASE_TARGET}.tar.gz"
+    assert expected_filename in curl_log_path.read_text(encoding="utf-8")
+
+    installed_binary = home_path / ".strix/bin/strix"
+    installed_result = subprocess.run(  # noqa: S603
+        [str(installed_binary), "--version"],
+        capture_output=True,
+        text=True,
+        check=True,
+    )
+    assert installed_result.stdout.strip() == f"strix {RELEASE_VERSION}"
+
+
+def test_installer_rejects_unsupported_architecture(tmp_path: Path) -> None:
+    repository_root = Path(__file__).resolve().parents[1]
+    archive_path = _create_release_archive(tmp_path)
+    mock_bin = _create_mock_commands(tmp_path, machine="riscv64")
+    environment, home_path, curl_log_path = _create_installer_environment(
+        tmp_path,
+        archive_path,
+        mock_bin,
+    )
+
+    result = _run_installer(repository_root, environment)
+
+    assert result.returncode != 0
+    assert "Unsupported OS/Arch: linux/riscv64" in result.stdout
+    assert not curl_log_path.exists()
+    assert not (home_path / ".strix").exists()

tests/test_llm_extra_headers.py

@@ -0,0 +1,97 @@
+"""Tests for LLM_EXTRA_HEADERS: custom default headers on OpenAI-compatible endpoints."""
+
+from __future__ import annotations
+
+import json
+from typing import TYPE_CHECKING
+
+import litellm
+import pytest
+from agents.models import _openai_shared
+
+from strix.config import loader
+from strix.config.loader import load_settings
+from strix.config.models import configure_sdk_model_defaults
+
+
+if TYPE_CHECKING:
+    from collections.abc import Iterator
+
+
+_ENV_KEYS = ["STRIX_LLM", "LLM_API_KEY", "LLM_API_BASE", "LLM_EXTRA_HEADERS"]
+
+
+@pytest.fixture(autouse=True)
+def _reset(monkeypatch: pytest.MonkeyPatch) -> Iterator[None]:
+    for key in _ENV_KEYS:
+        monkeypatch.delenv(key, raising=False)
+    monkeypatch.setattr(loader, "_cached", None)
+    monkeypatch.setattr(loader, "_override", None)
+
+    saved_headers = litellm.headers
+    saved_client = _openai_shared.get_default_openai_client()
+    litellm.headers = None
+    try:
+        yield
+    finally:
+        litellm.headers = saved_headers
+        _openai_shared.set_default_openai_client(saved_client)  # type: ignore[arg-type]
+
+
+def test_extra_headers_parsed_from_json_env(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("LLM_EXTRA_HEADERS", json.dumps({"X-A": "1", "X-B": "2"}))
+    settings = load_settings()
+    assert settings.llm.extra_headers == {"X-A": "1", "X-B": "2"}
+
+
+def test_extra_headers_merged_into_litellm_headers(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("STRIX_LLM", "litellm/openai/some-model")
+    monkeypatch.setenv("LLM_API_BASE", "https://gateway.example/v1")
+    monkeypatch.setenv("LLM_API_KEY", "token")
+    headers = {"X-Feature-Key": "svc", "X-Tenant": "acme"}
+    monkeypatch.setenv("LLM_EXTRA_HEADERS", json.dumps(headers))
+
+    configure_sdk_model_defaults(load_settings())
+
+    current: object = litellm.headers
+    assert isinstance(current, dict)
+    assert current["X-Feature-Key"] == "svc"
+    assert current["X-Tenant"] == "acme"
+
+
+def test_extra_headers_applied_to_native_openai_client(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("STRIX_LLM", "openai/some-model")
+    monkeypatch.setenv("LLM_API_BASE", "https://gateway.example/v1")
+    monkeypatch.setenv("LLM_API_KEY", "token")
+    monkeypatch.setenv("LLM_EXTRA_HEADERS", json.dumps({"X-Feature-Key": "svc"}))
+
+    configure_sdk_model_defaults(load_settings())
+
+    client = _openai_shared.get_default_openai_client()
+    assert client is not None
+    assert client.default_headers.get("X-Feature-Key") == "svc"
+    assert str(client.base_url).rstrip("/") == "https://gateway.example/v1"
+
+
+def test_extra_headers_applied_to_native_openai_without_custom_base(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    monkeypatch.setenv("STRIX_LLM", "openai/gpt-5")
+    monkeypatch.setenv("LLM_API_KEY", "token")
+    monkeypatch.setenv("LLM_EXTRA_HEADERS", json.dumps({"X-Feature-Key": "svc"}))
+
+    configure_sdk_model_defaults(load_settings())
+
+    client = _openai_shared.get_default_openai_client()
+    assert client is not None
+    assert client.default_headers.get("X-Feature-Key") == "svc"
+
+
+def test_no_extra_headers_leaves_litellm_headers_untouched(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("STRIX_LLM", "openai/some-model")
+    monkeypatch.setenv("LLM_API_BASE", "https://gateway.example/v1")
+    monkeypatch.setenv("LLM_API_KEY", "token")
+
+    configure_sdk_model_defaults(load_settings())
+
+    assert litellm.headers is None

tests/test_respond_to_user.py

@@ -0,0 +1,66 @@
+"""Tests for the ``respond_to_user`` yield tool."""
+
+from __future__ import annotations
+
+import json
+from typing import Any
+
+import pytest
+from agents.tool_context import ToolContext
+
+from strix.core.agents import AgentCoordinator
+from strix.tools.respond.tool import respond_to_user
+
+
+async def _call(context: dict[str, Any], message: str = "here is what I found") -> dict[str, Any]:
+    ctx = ToolContext(
+        context=context,
+        tool_name="respond_to_user",
+        tool_call_id="call-1",
+        tool_arguments="{}",
+    )
+    raw = await respond_to_user.on_invoke_tool(ctx, json.dumps({"message": message}))
+    return json.loads(raw)  # type: ignore[no-any-return]
+
+
+async def _context(*, interactive: bool, agent_id: str = "root") -> dict[str, Any]:
+    coordinator = AgentCoordinator()
+    await coordinator.register("root", "strix", parent_id=None)
+    return {"coordinator": coordinator, "agent_id": agent_id, "interactive": interactive}
+
+
+@pytest.mark.asyncio
+async def test_parks_the_agent_and_carries_the_message() -> None:
+    context = await _context(interactive=True)
+    result = await _call(context)
+
+    coordinator = context["coordinator"]
+    assert result["success"] is True
+    assert result["wait_outcome"] == "waiting"
+    assert result["message"] == "here is what I found"
+    assert coordinator.statuses["root"] == "waiting"
+    # Recorded as a human wait, so the driver never auto-resumes it.
+    assert coordinator.wait_kinds["root"] == "user"
+
+
+@pytest.mark.asyncio
+async def test_rejected_in_an_autonomous_run() -> None:
+    context = await _context(interactive=False)
+    result = await _call(context)
+
+    assert result["success"] is False
+    assert "finish_scan" in result["error"]
+    assert context["coordinator"].statuses["root"] == "running"
+
+
+@pytest.mark.asyncio
+async def test_a_message_that_already_arrived_is_taken_instead_of_parking() -> None:
+    context = await _context(interactive=True)
+    coordinator = context["coordinator"]
+    await coordinator.send("root", {"from": "user", "content": "wait, one more thing"})
+
+    result = await _call(context)
+
+    assert result["wait_outcome"] == "message_arrived"
+    assert result["pending_messages"] == 1
+    assert coordinator.statuses["root"] == "running"

tests/test_runner_rate_limit.py

@@ -14,6 +14,7 @@ import strix.tools.notes.tools as notes_tools
 import strix.tools.todo.tools as todo_tools
 from strix.core import runner
 from strix.core.agents import AgentCoordinator
+from strix.runtime import session_manager
 
 
 def _make_rate_limit_error() -> RateLimitError:
@@ -38,6 +39,8 @@ async def test_persistent_rate_limit_stops_gracefully(
             reasoning_effort="high",
             force_required_tool_choice=False,
             timeout=300,
+            prompt_cache=True,
+            extra_headers=None,
         ),
         runtime=types.SimpleNamespace(max_context_images=3),
     )
@@ -56,8 +59,8 @@ async def test_persistent_rate_limit_stops_gracefully(
     async def _cleanup(*_args: Any, **_kwargs: Any) -> None:
         return None
 
-    monkeypatch.setattr(runner.session_manager, "create_or_reuse", _create_or_reuse)  # type: ignore[attr-defined]
-    monkeypatch.setattr(runner.session_manager, "cleanup", _cleanup)  # type: ignore[attr-defined]
+    monkeypatch.setattr(session_manager, "create_or_reuse", _create_or_reuse)
+    monkeypatch.setattr(session_manager, "cleanup", _cleanup)
 
     monkeypatch.setattr(runner, "build_root_task", lambda _scan_config: "task")
     monkeypatch.setattr(runner, "build_scope_context", lambda _scan_config: "")

tests/test_runner_root_prompt.py

@@ -17,6 +17,7 @@ import strix.tools.notes.tools as notes_tools
 import strix.tools.todo.tools as todo_tools
 from strix.core import runner
 from strix.core.agents import AgentCoordinator
+from strix.runtime import session_manager
 
 
 def _make_rate_limit_error() -> RateLimitError:
@@ -46,6 +47,8 @@ def _patch_engine_scaffold(
             reasoning_effort="high",
             force_required_tool_choice=False,
             timeout=300,
+            prompt_cache=True,
+            extra_headers=None,
         ),
         runtime=types.SimpleNamespace(max_context_images=3),
     )
@@ -66,8 +69,8 @@ def _patch_engine_scaffold(
     async def _cleanup(*_args: Any, **_kwargs: Any) -> None:
         return None
 
-    monkeypatch.setattr(runner.session_manager, "create_or_reuse", _create_or_reuse)
-    monkeypatch.setattr(runner.session_manager, "cleanup", _cleanup)
+    monkeypatch.setattr(session_manager, "create_or_reuse", _create_or_reuse)
+    monkeypatch.setattr(session_manager, "cleanup", _cleanup)
 
     monkeypatch.setattr(runner, "build_root_task", lambda _scan_config: "task")
     monkeypatch.setattr(runner, "build_scope_context", lambda _scan_config: scope_context)

tests/test_update_check.py

@@ -159,14 +159,40 @@ def test_sha256_file(tmp_path: Path) -> None:
     assert update_check._sha256_file(path) == hashlib.sha256(b"strix").hexdigest()
 
 
-def test_release_target(monkeypatch: pytest.MonkeyPatch) -> None:
+@pytest.mark.parametrize(
+    ("system", "machine", "expected"),
+    [
+        ("Linux", "x86_64", "linux-x86_64"),
+        ("Linux", "aarch64", "linux-arm64"),
+        ("Linux", "arm64", "linux-arm64"),
+        ("Darwin", "arm64", "macos-arm64"),
+        ("Darwin", "riscv64", None),
+    ],
+)
+def test_release_target(
+    monkeypatch: pytest.MonkeyPatch,
+    system: str,
+    machine: str,
+    expected: str | None,
+) -> None:
+    monkeypatch.setattr(platform, "system", lambda: system)
+    monkeypatch.setattr(platform, "machine", lambda: machine)
+
+    assert update_check._release_target() == expected
+
+
+def test_self_update_uses_linux_arm64_release(monkeypatch: pytest.MonkeyPatch) -> None:
+    requested_update: list[tuple[str, str]] = []
+
+    def record_download(version: str, target: str, _console: Console) -> bool:
+        requested_update.append((version, target))
+        return True
+
+    monkeypatch.setattr(update_check, "is_binary_install", lambda: True)
+    monkeypatch.setattr(update_check, "get_version", lambda: "1.0.0")
     monkeypatch.setattr(platform, "system", lambda: "Linux")
-    monkeypatch.setattr(platform, "machine", lambda: "x86_64")
-    assert update_check._release_target() == "linux-x86_64"
+    monkeypatch.setattr(platform, "machine", lambda: "aarch64")
+    monkeypatch.setattr(update_check, "_download_and_replace", record_download)
 
-    monkeypatch.setattr(platform, "system", lambda: "Darwin")
-    monkeypatch.setattr(platform, "machine", lambda: "arm64")
-    assert update_check._release_target() == "macos-arm64"
-
-    monkeypatch.setattr(platform, "machine", lambda: "riscv64")
-    assert update_check._release_target() is None
+    assert update_check.self_update(Console(file=io.StringIO()), version="1.1.0") is True
+    assert requested_update == [("1.1.0", "linux-arm64")]

tests/test_viewer.py

@@ -4,9 +4,11 @@ from __future__ import annotations
 
 import json
 import os
+import sqlite3
 import urllib.error
 import urllib.request
 from typing import TYPE_CHECKING
+from urllib.parse import urlsplit
 
 from strix.core.paths import latest_run_dir, runs_base_dir
 from strix.interface.viewer.server import serve
@@ -86,6 +88,75 @@ def test_build_run_state_from_agents_json(tmp_path: Path) -> None:
     assert state["events"] == []
 
 
+def test_build_run_state_keeps_same_call_id_separate_per_agent(tmp_path: Path) -> None:
+    run_dir = _make_run(tmp_path, "tools", status="completed", end_time=None)
+    agents_db = run_dir / ".state" / "agents.db"
+    rows = [
+        (
+            "root",
+            {
+                "type": "function_call",
+                "call_id": "exec_command_0",
+                "name": "exec_command",
+                "arguments": json.dumps({"cmd": "echo root"}),
+            },
+        ),
+        (
+            "root",
+            {
+                "type": "function_call_output",
+                "call_id": "exec_command_0",
+                "output": json.dumps({"success": True, "output": "root"}),
+            },
+        ),
+        (
+            "child",
+            {
+                "type": "function_call",
+                "call_id": "exec_command_0",
+                "name": "exec_command",
+                "arguments": json.dumps({"cmd": "echo child"}),
+            },
+        ),
+        (
+            "child",
+            {
+                "type": "function_call_output",
+                "call_id": "exec_command_0",
+                "output": json.dumps({"success": True, "output": "child"}),
+            },
+        ),
+    ]
+    with sqlite3.connect(agents_db) as conn:
+        conn.execute(
+            """
+            create table agent_messages (
+                id integer primary key,
+                session_id text not null,
+                message_data text not null,
+                created_at text not null
+            )
+            """
+        )
+        conn.executemany(
+            """
+            insert into agent_messages (session_id, message_data, created_at)
+            values (?, ?, '2026-01-01T00:00:00+00:00')
+            """,
+            [(agent_id, json.dumps(message)) for agent_id, message in rows],
+        )
+
+    state = build_run_state(run_dir)
+    tools = [event for event in state["events"] if event["type"] == "tool"]
+
+    assert len(tools) == 2
+    by_agent = {event["agent_id"]: event for event in tools}
+    assert by_agent["root"]["data"]["args"] == {"cmd": "echo root"}
+    assert by_agent["root"]["data"]["result"]["output"] == "root"
+    assert by_agent["child"]["data"]["args"] == {"cmd": "echo child"}
+    assert by_agent["child"]["data"]["result"]["output"] == "child"
+
+
 def _get(url: str, *, cookie: str | None = None) -> tuple[int, str, bytes]:
     headers = {"Cookie": cookie} if cookie else {}
     req = urllib.request.Request(url, headers=headers)  # noqa: S310 - localhost test server
@@ -271,6 +342,11 @@ def _session_cookie(url: str, token: str) -> str:
     return raw.split(";", 1)[0]
 
 
+def _cookie_name(url: str) -> str:
+    """The per-server session cookie name, derived from the bound port."""
+    return f"strix_viewer_session_{urlsplit(url).port}"
+
+
 def _get_status(url: str, *, cookie: str | None = None) -> int:
     headers = {"Cookie": cookie} if cookie else {}
     req = urllib.request.Request(url, headers=headers)  # noqa: S310 - localhost test server
@@ -311,7 +387,7 @@ def test_capability_issued_only_for_tokened_bootstrap(
         # Only the correct bootstrap token mints the session cookie.
         with urllib.request.urlopen(f"{url}/?token={token}") as resp:  # noqa: S310  # nosec B310
             cookie = str(resp.headers.get("Set-Cookie", ""))
-        assert "strix_viewer_session=" in cookie
+        assert f"{_cookie_name(url)}=" in cookie
         assert "HttpOnly" in cookie and "SameSite=Strict" in cookie
 
         # Static assets never carry it.
@@ -344,7 +420,7 @@ def test_unauthorized_client_cannot_acquire_capability(
             url,
             "/api/agents/steer",
             {"agent_id": "root", "message": "pwn"},
-            cookie="strix_viewer_session=",
+            cookie=f"{_cookie_name(url)}=",
         )
         assert status == 403
         assert delivered == []
@@ -541,6 +617,53 @@ def test_runs_list_requires_session_and_verification(
         httpd.server_close()
 
 
+def test_concurrent_servers_use_distinct_cookies(
+    tmp_path: Path, monkeypatch: pytest.MonkeyPatch
+) -> None:
+    """Cookies are host-scoped, not port-scoped: two viewers on 127.0.0.1 must
+    not share a cookie slot, and one server's cookie must not pass the other's
+    session gate."""
+    run_a = _make_run(tmp_path / "a", "run-a", status="running", end_time=None)
+    run_b = _make_run(tmp_path / "b", "run-b", status="running", end_time=None)
+    _bundle(tmp_path, monkeypatch)
+    monkeypatch.setattr(
+        "strix.interface.viewer.auth.read_auth", lambda: {"email": "a@b.com", "token": "t"}
+    )
+    monkeypatch.setattr("strix.interface.viewer.auth.is_verified", lambda: True)
+
+    httpd_a, url_a, token_a = serve(run_a, open_browser=False)
+    httpd_b, url_b, token_b = serve(run_b, open_browser=False)
+    try:
+        cookie_a = _session_cookie(url_a, token_a)
+        cookie_b = _session_cookie(url_b, token_b)
+
+        # The two servers mint differently named cookies, so a browser stores both.
+        assert cookie_a.split("=", 1)[0] == _cookie_name(url_a)
+        assert cookie_b.split("=", 1)[0] == _cookie_name(url_b)
+        assert cookie_a.split("=", 1)[0] != cookie_b.split("=", 1)[0]
+
+        def _status(url: str, cookie: str) -> dict[str, object]:
+            _, _, body = _get(f"{url}/api/auth/status", cookie=cookie)
+            return dict(json.loads(body))
+
+        # Each server honors its own cookie...
+        assert _status(url_a, cookie_a)["verified"] is True
+        assert _status(url_b, cookie_b)["verified"] is True
+        # ...but treats the other server's cookie as session-less.
+        assert _status(url_a, cookie_b)["verified"] is False
+        assert _status(url_b, cookie_a)["verified"] is False
+        # Even both cookies together (what a real browser would send) only
+        # match the token minted by the receiving server.
+        both = f"{cookie_a}; {cookie_b}"
+        assert _status(url_a, both)["verified"] is True
+        assert _status(url_b, both)["verified"] is True
+    finally:
+        httpd_a.shutdown()
+        httpd_a.server_close()
+        httpd_b.shutdown()
+        httpd_b.server_close()
+
+
 def test_server_rejects_path_traversal(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
     run_dir = _make_run(tmp_path, "guard", status="completed", end_time="2026-01-01T00:00:00Z")
     secret = tmp_path / "secret.txt"

uv.lock

@@ -2411,7 +2411,7 @@ wheels = [
 
 [[package]]
 name = "strix-agent"
-version = "1.3.1"
+version = "1.4.1"
 source = { editable = "." }
 dependencies = [
     { name = "caido-sdk-client" },