Files
strix/strix/tools/agents_graph/tools.py
T
0xallam c8a0be4716 chore(orchestration): drop XML wrappers + close remaining audit gaps
Final pass after re-audit. Three sub-specs landed:

**XML simplification** — the legacy XML envelopes were prompt-engineering
ceremony, not parser primitives (the SDK uses native tool-calling). Drop
the verbose wrappers in favor of one-liner labeled headers. Side benefit:
fixes the unescaped-content XML-injection bug the audit caught (peer
content containing ``</content>`` no longer breaks the wrapper).

- ``_format_inter_agent_message``: ``<inter_agent_message><sender>...
  <content>...`` 9-line XML → ``[Message from {name} ({id}) | type=... |
  priority=...]\n{content}``.
- ``_render_completion_report``: ``<agent_completion_report><agent_info>
  ...<results>...`` XML → human-readable structured text with section
  headers and bulleted lists.
- ``inherited_context``: ``<inherited_context_from_parent>...`` →
  ``== Inherited context from parent (background only) ==``.

**MG1: TUI stop-agent uses graceful cancel.** ``tui.py`` was calling
``bus.cancel_descendants`` (hard, ``task.cancel()`` mid-stream) for the
stop-agent button. Switched to ``bus.cancel_descendants_graceful``, which
uses ``RunResultStreaming.cancel(mode="after_turn")`` to let each agent
finish its current turn (and save to session) before honoring the cancel.
The hard path remains in ``entry.py`` for KeyboardInterrupt where
graceful isn't possible.

**MG2: Document hook lock-free stats mutation.** Added a comment in
``hooks.on_llm_start`` explaining why ``warned_85`` / ``warned_final``
are mutated lock-free: SDK serializes ``on_llm_start`` per agent, so this
hook is the sole writer to those keys; ``record_usage`` only writes
disjoint keys (in/out/cached/calls).

**AG3: Auto-load ``coordination/root_agent`` skill for the root.**
Legacy auto-loaded the orchestration-guidance skill for root agents
only. Threaded ``is_root`` through ``render_system_prompt`` →
``_resolve_skills``; root agents now get the skill, children don't.

Skipped (per user direction): whitebox-wiki integration (CG2-4) — the
auto-injection / auto-update of the shared repo wiki was a pre-migration
feature; user opted not to restore it.
2026-04-25 17:48:55 -07:00

746 lines
25 KiB
Python

"""Multi-agent graph tools — read/write the :class:`AgentMessageBus`.
- ``view_agent_graph``: render the parent/child tree.
- ``agent_status``: per-agent status + pending message count.
- ``send_message_to_agent``: queue a message in another agent's inbox.
- ``wait_for_message``: pause this agent until a message arrives or
``timeout_seconds`` elapses.
- ``create_agent``: spawn a child via
``asyncio.create_task(Runner.run(...))``; the task handle is stored
so a root-level cancel cascades to descendants.
- ``agent_finish``: subagents only — flips ``agent_finish_called`` so
the ``on_agent_end`` hook records "completed" rather than "crashed",
and posts a structured completion report to the parent's inbox.
"""
from __future__ import annotations
import asyncio
import json
import logging
import uuid
from datetime import UTC, datetime
from typing import TYPE_CHECKING, Any, Literal
from agents import RunContextWrapper, function_tool
from agents.items import TResponseInputItem
from strix.orchestration.hooks import StrixOrchestrationHooks
from strix.orchestration.run_loop import run_with_continuation
from strix.run_config_factory import make_agent_context, make_run_config
if TYPE_CHECKING:
from collections.abc import Callable
from agents import Agent as SDKAgent
logger = logging.getLogger(__name__)
def _ctx(ctx: RunContextWrapper) -> dict[str, Any]:
return ctx.context if isinstance(ctx.context, dict) else {}
def _render_completion_report(
*,
agent_name: str,
agent_id: str,
task: str,
success: bool,
result_summary: str,
findings: list[str],
recommendations: list[str],
) -> str:
"""Render a child's completion report as plain structured text.
Goes into the parent's bus inbox; the inject filter prepends a
``[Message from ...]`` header on top, so this body just carries the
contents. No XML — no escaping concerns, no parser ambiguity.
"""
status = "SUCCESS" if success else "FAILED"
completion_time = datetime.now(UTC).isoformat()
lines: list[str] = [
f"== Completion report from {agent_name} ({agent_id}) ==",
f"Status: {status}",
f"Time: {completion_time}",
]
if task:
lines.append(f"Task: {task}")
lines.append("")
lines.append("Summary:")
lines.append(result_summary or "(none)")
if findings:
lines.append("")
lines.append("Findings:")
lines.extend(f"- {f}" for f in findings)
if recommendations:
lines.append("")
lines.append("Recommendations:")
lines.extend(f"- {r}" for r in recommendations)
return "\n".join(lines)
@function_tool(timeout=30)
async def view_agent_graph(ctx: RunContextWrapper) -> str:
"""Print the multi-agent tree — every agent, its parent, its status.
Use before spawning a new agent (don't duplicate work — check whether
something specialized for that task already exists) and any time you
want a snapshot of who's still ``running`` / ``waiting`` /
``completed`` / ``crashed`` / ``stopped``. Output is an indented
bullet list with status in brackets; the agent that called this tool
is marked ``← you``.
"""
inner = _ctx(ctx)
bus = inner.get("bus")
me = inner.get("agent_id")
if bus is None:
return json.dumps(
{"success": False, "error": "Bus not initialized in context."},
ensure_ascii=False,
default=str,
)
async with bus._lock:
parent_of = dict(bus.parent_of)
statuses = dict(bus.statuses)
names = dict(bus.names)
lines: list[str] = []
def render(aid: str, depth: int) -> None:
status = statuses.get(aid, "?")
marker = " ← you" if aid == me else ""
lines.append(f"{' ' * depth}- {names.get(aid, aid)} ({aid}) [{status}]{marker}")
for child, p in parent_of.items():
if p == aid:
render(child, depth + 1)
roots = [aid for aid, parent in parent_of.items() if parent is None]
for root in roots:
render(root, 0)
summary = {
"total": len(parent_of),
"running": sum(1 for s in statuses.values() if s == "running"),
"waiting": sum(1 for s in statuses.values() if s == "waiting"),
"completed": sum(1 for s in statuses.values() if s == "completed"),
"crashed": sum(1 for s in statuses.values() if s == "crashed"),
"stopped": sum(1 for s in statuses.values() if s == "stopped"),
}
return json.dumps(
{
"success": True,
"graph_structure": "\n".join(lines) or "(no agents)",
"summary": summary,
},
ensure_ascii=False,
default=str,
)
@function_tool(timeout=30)
async def agent_status(ctx: RunContextWrapper, agent_id: str) -> str:
"""Look up one agent's lifecycle state + pending message count.
Use when you need precise state on a specific agent (e.g., "is the
XSS specialist still going?") rather than the full tree view.
Returns ``status`` (``running`` / ``waiting`` / ``completed`` /
``crashed`` / ``stopped``), ``parent_id``, and ``pending_messages``.
Args:
agent_id: The 8-char id from ``view_agent_graph`` /
``create_agent``.
"""
inner = _ctx(ctx)
bus = inner.get("bus")
if bus is None:
return json.dumps(
{"success": False, "error": "Bus not initialized in context."},
ensure_ascii=False,
default=str,
)
async with bus._lock:
if agent_id not in bus.statuses:
return json.dumps(
{
"success": False,
"error": f"Unknown agent_id: {agent_id}",
},
ensure_ascii=False,
default=str,
)
return json.dumps(
{
"success": True,
"agent_id": agent_id,
"name": bus.names.get(agent_id),
"status": bus.statuses.get(agent_id),
"parent_id": bus.parent_of.get(agent_id),
"pending_messages": len(bus.inboxes.get(agent_id, [])),
},
ensure_ascii=False,
default=str,
)
@function_tool(timeout=30)
async def send_message_to_agent(
ctx: RunContextWrapper,
target_agent_id: str,
message: str,
message_type: Literal["query", "instruction", "information"] = "information",
priority: Literal["low", "normal", "high", "urgent"] = "normal",
) -> str:
"""Send a message to another agent's inbox — sparingly.
Inter-agent messages are surfaced at the top of the target's next
LLM turn. Use only when essential:
- Sharing a discovered finding/credential another agent needs.
- Asking a specialist a focused question.
- Coordinating who covers what (avoid overlap).
- Telling a child to wrap up or change course.
**Don't** use for routine "hello/status" pings, for context the
target already has (children inherit parent history), or when
parent/child completion via ``agent_finish`` already covers the
flow. Messages to a finalized agent are dropped.
Args:
target_agent_id: Recipient's 8-char id.
message: The full message body. Be specific — include payloads,
URLs, or what you want them to do, not just headlines.
message_type: ``query`` (you want a reply), ``instruction``
(you're directing them), ``information`` (FYI, no reply
expected). Default ``information``.
priority: ``low`` / ``normal`` / ``high`` / ``urgent``.
"""
inner = _ctx(ctx)
bus = inner.get("bus")
me = inner.get("agent_id")
if bus is None or me is None:
return json.dumps(
{"success": False, "error": "Bus or agent_id missing in context."},
ensure_ascii=False,
default=str,
)
async with bus._lock:
if target_agent_id not in bus.statuses:
return json.dumps(
{
"success": False,
"error": f"Target agent '{target_agent_id}' not found.",
},
ensure_ascii=False,
default=str,
)
target_status = bus.statuses.get(target_agent_id)
if target_status in ("completed", "crashed", "stopped"):
return json.dumps(
{
"success": False,
"error": f"Target agent '{target_agent_id}' is {target_status}; message dropped.",
},
ensure_ascii=False,
default=str,
)
msg_id = f"msg_{uuid.uuid4().hex[:8]}"
await bus.send(
target_agent_id,
{
"id": msg_id,
"from": me,
"content": message,
"type": message_type,
"priority": priority,
},
)
return json.dumps(
{
"success": True,
"message_id": msg_id,
"target_agent_id": target_agent_id,
"delivery_status": "queued",
},
ensure_ascii=False,
default=str,
)
# Tighter would burn CPU; slacker would feel laggy when a sibling
# delivers a message right after the wait starts.
_WAIT_POLL_SECONDS = 1.0
@function_tool(timeout=601)
async def wait_for_message(
ctx: RunContextWrapper,
reason: str = "Waiting for messages from other agents",
timeout_seconds: int = 600,
) -> str:
"""Pause this agent until a message lands in its inbox (or timeout).
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.
**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.
- 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.
- Children update the parent automatically via ``agent_finish``
→ no extra coordination needed.
Args:
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: Hard cap (default 600s). On timeout the tool
returns and you decide whether to keep working or wait
again.
"""
inner = _ctx(ctx)
bus = inner.get("bus")
me = inner.get("agent_id")
if bus is None or me is None:
return json.dumps(
{"success": False, "error": "Bus or agent_id missing in context."},
ensure_ascii=False,
default=str,
)
async with bus._lock:
bus.statuses[me] = "waiting"
deadline = asyncio.get_event_loop().time() + timeout_seconds
try:
while asyncio.get_event_loop().time() < deadline:
async with bus._lock:
pending = len(bus.inboxes.get(me, []))
if pending > 0:
async with bus._lock:
bus.statuses[me] = "running"
return json.dumps(
{
"success": True,
"status": "message_arrived",
"pending_messages": pending,
"reason": reason,
},
ensure_ascii=False,
default=str,
)
await asyncio.sleep(_WAIT_POLL_SECONDS)
finally:
async with bus._lock:
# Don't clobber a status another writer set (e.g., on_agent_end
# finalized us as ``stopped`` mid-wait).
if bus.statuses.get(me) == "waiting":
bus.statuses[me] = "running"
return json.dumps(
{
"success": True,
"status": "timeout",
"timeout_seconds": timeout_seconds,
"reason": reason,
"note": "No messages within timeout — continue work or call agent_finish.",
},
ensure_ascii=False,
default=str,
)
@function_tool(timeout=120)
async def create_agent(
ctx: RunContextWrapper,
name: str,
task: str,
inherit_context: bool = True,
skills: list[str] | None = None,
) -> str:
"""Spawn a specialist child agent to run in parallel.
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
working in parallel). When the child calls ``agent_finish``, its
completion report lands in the parent's inbox.
**Before spawning, call ``view_agent_graph``** to confirm no
existing agent already covers this scope — duplicate specialists
waste turns and create coordination headaches.
**Specialization principles:**
- Most agents need at least one ``skill`` to be useful.
- Aim for **1-3 related skills** per agent. Up to 5 only when the
task genuinely spans them.
- One skill = most focused (e.g., XSS-only). Five skills = upper
bound.
- Match the ``name`` to the focus (``XSS Specialist``,
``SQLi Validator``, ``Auth Specialist``).
**When to spawn vs do it yourself:**
- Spawn when the subtask is large, parallelizable, or needs
different specialization than what you're already doing.
- Don't spawn for trivial one-shot probes — just run the tool
yourself.
Args:
name: Human-readable child name (used in graph views and
``send_message_to_agent`` flows).
task: Specific objective. Be concrete — what to test, what
success looks like, any constraints.
inherit_context: Default ``True``. The child receives the
parent's input history as background; only set ``False``
when starting a clean-slate task.
skills: Comma-separated skill names. Max 5; prefer 1-3.
"""
inner = _ctx(ctx)
bus = inner.get("bus")
parent_id = inner.get("agent_id")
factory: Callable[..., SDKAgent] | None = inner.get("agent_factory")
if bus is None or parent_id is None:
return json.dumps(
{"success": False, "error": "Bus or agent_id missing in context."},
ensure_ascii=False,
default=str,
)
if factory is None:
return json.dumps(
{
"success": False,
"error": (
"No agent_factory in context. "
"The root assembly must inject one via make_agent_context."
),
},
ensure_ascii=False,
default=str,
)
child_id = uuid.uuid4().hex[:8]
try:
child_agent = factory(name=name, skills=skills or [])
except Exception as e:
logger.exception("agent_factory raised while building child '%s'", name)
return json.dumps(
{
"success": False,
"error": f"agent_factory failed: {e!s}",
},
ensure_ascii=False,
default=str,
)
await bus.register(child_id, name, parent_id)
# ``ctx.turn_input`` carries the parent's full conversation up to and
# including the call that's currently invoking ``create_agent``
# (populated by SDK at ``run_internal/turn_resolution.py:806``).
# Wrap as a single read-only block so the child sees the parent's
# reasoning as background but doesn't try to continue parent's turns.
parent_history = list(ctx.turn_input) if inherit_context and ctx.turn_input else []
initial_input: list[TResponseInputItem] = []
if parent_history:
rendered = json.dumps(parent_history, ensure_ascii=False, default=str)
initial_input.append(
{
"role": "user",
"content": (
"== Inherited context from parent (background only) ==\n"
f"{rendered}\n"
"== End of inherited context ==\n"
"Use the above as background only; do not continue the "
"parent's work. Your task follows."
),
},
)
initial_input.append(
{
"role": "user",
"content": (
f"You are agent {name} ({child_id}); your parent is {parent_id}. "
f"Maintain your own identity. Call agent_finish when your task "
f"is complete."
),
}
)
initial_input.append({"role": "user", "content": task})
child_ctx = make_agent_context(
bus=bus,
sandbox_session=inner.get("sandbox_session"),
sandbox_client=inner.get("sandbox_client"),
caido_client=inner.get("caido_client"),
agent_id=child_id,
parent_id=parent_id,
tracer=inner.get("tracer"),
model=inner["model"],
model_settings=inner.get("model_settings"),
max_turns=int(inner.get("max_turns", 300)),
is_whitebox=bool(inner.get("is_whitebox", False)),
interactive=bool(inner.get("interactive", False)),
diff_scope=inner.get("diff_scope"),
run_id=inner.get("run_id"),
agent_factory=factory,
)
# Stash the task string for ``agent_finish`` to echo back in its
# XML completion report.
child_ctx["task"] = task
child_run_config = make_run_config(
sandbox_session=inner.get("sandbox_session"),
sandbox_client=inner.get("sandbox_client"),
model=inner["model"],
model_settings_override=inner.get("model_settings"),
)
task_handle = asyncio.create_task(
run_with_continuation(
agent=child_agent,
initial_input=initial_input,
run_config=child_run_config,
context=child_ctx,
hooks=StrixOrchestrationHooks(),
max_turns=int(inner.get("max_turns", 300)),
bus=bus,
agent_id=child_id,
interactive=bool(inner.get("interactive", False)),
),
name=f"agent-{name}-{child_id}",
)
async with bus._lock:
bus.tasks[child_id] = task_handle
return json.dumps(
{
"success": True,
"agent_id": child_id,
"name": name,
"parent_id": parent_id,
"message": f"Spawned '{name}' ({child_id}) running in parallel.",
},
ensure_ascii=False,
default=str,
)
@function_tool(timeout=30)
async def agent_finish(
ctx: RunContextWrapper,
result_summary: str,
findings: list[str] | None = None,
success: bool = True,
report_to_parent: bool = True,
final_recommendations: list[str] | None = None,
) -> str:
"""Subagent termination — post a completion report to the parent.
**Subagents only.** Root agents must call ``finish_scan`` instead;
this tool refuses to run for root agents. Calling this:
1. Marks the subagent as ``completed``.
2. Posts a structured completion report to the parent's inbox
(when ``report_to_parent`` is true).
3. Stops this subagent's execution.
**Vulnerability findings must already be filed via
``create_vulnerability_report`` before calling this.** The
``findings`` field here is for narrative summary only — it does
not register vulns in the scan report.
Write the summary as if the parent has no idea what you were
doing: what did you test, what did you find/confirm/rule out,
what's still open.
Args:
result_summary: What you accomplished and discovered. Concrete
and specific (URLs, parameters, payloads that worked).
findings: Optional bullet list of confirmed observations. For
credit-bearing vulnerabilities, file
``create_vulnerability_report`` first; this is for
narrative.
success: Whether the assigned subtask was completed
successfully. Default ``True``.
report_to_parent: Whether to deliver the completion report to
the parent's inbox. Default ``True``.
final_recommendations: Optional next-step suggestions for the
parent (e.g., "prioritize testing X", "spawn an agent to
cover Y").
"""
inner = _ctx(ctx)
bus = inner.get("bus")
me = inner.get("agent_id")
if bus is None or me is None:
return json.dumps(
{"success": False, "error": "Bus or agent_id missing in context."},
ensure_ascii=False,
default=str,
)
parent_id = inner.get("parent_id")
if parent_id is None:
return json.dumps(
{
"success": False,
"agent_completed": False,
"error": (
"agent_finish is for subagents. Root/main agents must call finish_scan instead."
),
"parent_notified": False,
},
ensure_ascii=False,
default=str,
)
# ``agent_finish_called`` is set by ``StrixOrchestrationHooks.on_tool_end``;
# no need to set it here.
parent_notified = False
if report_to_parent:
async with bus._lock:
agent_name = bus.names.get(me, me)
report = _render_completion_report(
agent_name=agent_name,
agent_id=me,
task=str(inner.get("task", "")),
success=success,
result_summary=result_summary,
findings=list(findings or []),
recommendations=list(final_recommendations or []),
)
await bus.send(
parent_id,
{
"id": f"report_{uuid.uuid4().hex[:8]}",
"from": me,
"content": report,
"type": "completion",
"priority": "high",
},
)
parent_notified = True
return json.dumps(
{
"success": True,
"agent_completed": True,
"parent_notified": parent_notified,
"agent_id": me,
"summary": result_summary,
"findings_count": len(findings or []),
"has_recommendations": bool(final_recommendations),
},
ensure_ascii=False,
default=str,
)
@function_tool(timeout=30)
async def stop_agent(
ctx: RunContextWrapper,
target_agent_id: str,
cascade: bool = True,
reason: str = "",
) -> str:
"""Gracefully stop a running agent (and optionally its descendants).
Uses the SDK's ``RunResultStreaming.cancel(mode="after_turn")`` so the
target's current turn finishes — including saving items to its
session — before the run loop honors the cancel. The agent's
interactive outer loop sees ``stopping`` and exits without awaiting
more messages, so ``on_agent_end`` finalizes with status="stopped".
Use sparingly. Prefer ``send_message_to_agent`` (asking the agent
to wrap up) for soft-stop scenarios. Reach for ``stop_agent`` when
a child has gone off-track and won't self-correct.
Args:
target_agent_id: The 8-char id from ``view_agent_graph`` /
``create_agent``. Cannot stop yourself.
cascade: If ``True`` (default), also stop every descendant of
``target_agent_id`` leaves-first. ``False`` stops only the
target.
reason: Optional human-readable reason for the stop, surfaced
in logs and telemetry.
"""
inner = _ctx(ctx)
bus = inner.get("bus")
me = inner.get("agent_id")
if bus is None or me is None:
return json.dumps(
{"success": False, "error": "Bus or agent_id missing in context."},
ensure_ascii=False,
default=str,
)
if target_agent_id == me:
return json.dumps(
{
"success": False,
"error": "Cannot stop yourself; call agent_finish or finish_scan instead.",
},
ensure_ascii=False,
default=str,
)
async with bus._lock:
if target_agent_id not in bus.statuses:
return json.dumps(
{"success": False, "error": f"Unknown agent_id: {target_agent_id}"},
ensure_ascii=False,
default=str,
)
target_status = bus.statuses.get(target_agent_id)
if target_status in ("completed", "crashed", "stopped"):
return json.dumps(
{
"success": False,
"error": f"Target agent '{target_agent_id}' is already {target_status}.",
},
ensure_ascii=False,
default=str,
)
if cascade:
await bus.cancel_descendants_graceful(target_agent_id)
else:
async with bus._lock:
bus.stopping.add(target_agent_id)
await bus.request_interrupt(target_agent_id, mode="after_turn")
logger.info(
"stop_agent: target=%s cascade=%s reason=%r",
target_agent_id,
cascade,
reason,
)
return json.dumps(
{
"success": True,
"target_agent_id": target_agent_id,
"cascade": cascade,
"reason": reason,
"note": "Cancellation is graceful — current turn completes first.",
},
ensure_ascii=False,
default=str,
)