mirror of
https://github.com/usestrix/strix.git
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277 lines
8.8 KiB
Python
277 lines
8.8 KiB
Python
"""``build_strix_agent`` — assemble an ``agents.Agent`` for root or child.
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Wires the SDK function tools, multi-agent graph tools, and the rendered
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Jinja prompt into one ``agents.Agent`` ready for ``Runner.run``.
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Two flavors:
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- **Root** (``is_root=True``): top-level scan agent. Carries
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``finish_scan`` and stops after that tool reports ``scan_completed``.
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- **Child** (``is_root=False``): subagents spawned by the
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``create_agent`` graph tool. Carries ``agent_finish`` and stops
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after that tool reports ``agent_completed``.
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Skills are baked into the system prompt at scan bring-up; there's no
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runtime skill-loading tool.
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"""
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from __future__ import annotations
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import json
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import logging
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from typing import TYPE_CHECKING, Any
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from agents.agent import ToolsToFinalOutputResult
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from agents.sandbox import SandboxAgent
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from agents.sandbox.capabilities import Filesystem, Shell
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from agents.tool import Tool
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from strix.agents.prompt import render_system_prompt
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from strix.tools.agents_graph.tools import (
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agent_finish,
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create_agent,
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send_message_to_agent,
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stop_agent,
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view_agent_graph,
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wait_for_message,
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)
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from strix.tools.finish.tool import finish_scan
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from strix.tools.notes.tools import (
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create_note,
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delete_note,
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get_note,
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list_notes,
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update_note,
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)
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from strix.tools.proxy.tools import (
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list_requests,
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repeat_request,
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scope_rules,
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send_request,
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view_request,
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)
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from strix.tools.python.tool import python_action
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from strix.tools.reporting.tool import create_vulnerability_report
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from strix.tools.thinking.tool import think
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from strix.tools.todo.tools import (
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create_todo,
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delete_todo,
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list_todos,
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mark_todo_done,
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mark_todo_pending,
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update_todo,
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)
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from strix.tools.web_search.tool import web_search
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if TYPE_CHECKING:
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from agents import RunContextWrapper
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from agents.tool import FunctionToolResult
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logger = logging.getLogger(__name__)
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def _lifecycle_tool_completed(tool_name: str, output: Any) -> bool:
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if tool_name == "agent_finish":
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completion_key = "agent_completed"
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elif tool_name == "finish_scan":
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completion_key = "scan_completed"
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else:
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return False
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if not isinstance(output, str):
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return False
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try:
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parsed = json.loads(output)
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except (TypeError, ValueError):
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return False
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return bool(isinstance(parsed, dict) and parsed.get("success") and parsed.get(completion_key))
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def _wait_tool_parked(tool_name: str, output: Any) -> bool:
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if tool_name != "wait_for_message" or not isinstance(output, str):
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return False
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try:
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parsed = json.loads(output)
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except (TypeError, ValueError):
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return False
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return bool(
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isinstance(parsed, dict)
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and parsed.get("success")
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and parsed.get("agent_waiting")
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and parsed.get("status") == "waiting"
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)
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def _finish_tool_use_behavior(
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ctx: RunContextWrapper[Any],
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tool_results: list[FunctionToolResult],
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) -> ToolsToFinalOutputResult:
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"""Stop only after a lifecycle tool reports successful completion."""
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interactive = (
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bool(ctx.context.get("interactive", False)) if isinstance(ctx.context, dict) else False
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)
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for tool_result in tool_results:
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if _lifecycle_tool_completed(tool_result.tool.name, tool_result.output):
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return ToolsToFinalOutputResult(
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is_final_output=True,
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final_output=tool_result.output,
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)
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if interactive and _wait_tool_parked(tool_result.tool.name, tool_result.output):
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return ToolsToFinalOutputResult(
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is_final_output=True,
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final_output=tool_result.output,
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)
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return ToolsToFinalOutputResult(is_final_output=False, final_output=None)
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# Host-side Strix tools. Sandbox shell + filesystem are added per-run
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# by the SDK via the ``Shell`` and ``Filesystem`` capabilities below
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# (they bind to the live sandbox session and emit ``exec_command`` /
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# ``write_stdin`` / ``apply_patch`` / ``view_image`` function tools).
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_BASE_TOOLS: tuple[Tool, ...] = (
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# Thinking + planning
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think,
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# Per-agent todos
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create_todo,
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list_todos,
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update_todo,
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mark_todo_done,
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mark_todo_pending,
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delete_todo,
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# Shared notes (per-run JSONL store)
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create_note,
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list_notes,
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get_note,
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update_note,
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delete_note,
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# Web search (only registered if PERPLEXITY_API_KEY is set; the
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# tool itself returns a structured error when not configured, so
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# always exposing it is safe)
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web_search,
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# Reporting
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create_vulnerability_report,
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# Caido HTTP/HTTPS proxy
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list_requests,
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view_request,
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send_request,
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repeat_request,
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scope_rules,
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# Stateless Python execution with proxy helpers pre-bound
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python_action,
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# Multi-agent graph tools (the coordinator is in ctx.context)
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view_agent_graph,
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send_message_to_agent,
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wait_for_message,
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create_agent,
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stop_agent,
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)
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def build_strix_agent(
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*,
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name: str = "strix",
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skills: list[str] | None = None,
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is_root: bool,
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scan_mode: str = "deep",
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is_whitebox: bool = False,
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interactive: bool = False,
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system_prompt_context: dict[str, Any] | None = None,
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) -> SandboxAgent[Any]:
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"""Build a ``SandboxAgent`` configured for either root or child use.
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The ``Shell`` and ``Filesystem`` capabilities are added unbound; the
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SDK's runtime binds them per-run against the live sandbox session
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set on ``RunConfig.sandbox`` and merges their tools (``exec_command``,
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``write_stdin``, ``apply_patch``, ``view_image``) into the agent's
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final tool list. We deliberately exclude ``Compaction`` (OpenAI
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Responses API only).
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Args:
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name: Agent name. Surfaces in traces and the coordinator's ``names`` map.
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Defaults to ``"strix"`` for the root; create_agent passes
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distinct names per child.
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skills: Skills to preload into the system prompt.
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is_root: Selects the tool list and ``tool_use_behavior``.
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Root carries ``finish_scan`` and child carries ``agent_finish``;
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the run only stops when the lifecycle tool result succeeds.
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scan_mode: ``"deep"`` etc.; routes the scan-mode skill section
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of the prompt template.
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is_whitebox: Whitebox source-aware mode toggle. Adds two extra
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skills to the prompt and gates whitebox-only behavior in
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the create_agent / wiki integration.
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interactive: Renders the interactive-mode communication block
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in the system prompt.
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system_prompt_context: Free-form dict the prompt template
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renders into the ``system_prompt_context`` variable —
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today carries the scan scope / authorization block.
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"""
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instructions = render_system_prompt(
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skills=skills,
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scan_mode=scan_mode,
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is_whitebox=is_whitebox,
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is_root=is_root,
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interactive=interactive,
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system_prompt_context=system_prompt_context,
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)
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if is_root:
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tools: list[Tool] = [*_BASE_TOOLS, finish_scan]
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else:
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tools = [*_BASE_TOOLS, agent_finish]
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logger.info(
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"Built %s agent '%s' (skills=%d, tools=%d, scan_mode=%s, whitebox=%s)",
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"root" if is_root else "child",
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name,
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len(skills or []),
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len(tools),
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scan_mode,
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is_whitebox,
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)
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return SandboxAgent(
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name=name,
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instructions=instructions,
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tools=tools,
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tool_use_behavior=_finish_tool_use_behavior,
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# Non-interactive runs must keep forcing tool calls until the
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# lifecycle tool completes. Interactive runs need the SDK default
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# reset so a tool-assisted answer can end as plain text instead of
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# looping through think/list_todos forever.
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reset_tool_choice=interactive,
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# model=None so ``RunConfig.model`` drives provider selection
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# through the SDK's default MultiProvider.
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model=None,
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capabilities=[Filesystem(), Shell()],
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)
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def make_child_factory(
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*,
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scan_mode: str = "deep",
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is_whitebox: bool = False,
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interactive: bool = False,
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system_prompt_context: dict[str, Any] | None = None,
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) -> Any:
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"""Return the runner-owned builder used by ``spawn_child_agent``.
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Run-level arguments (``scan_mode``, ``is_whitebox``, etc.) are
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captured in a closure so each child inherits scan-level configuration
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without the graph tool knowing about runner internals.
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"""
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def _factory(*, name: str, skills: list[str]) -> SandboxAgent[Any]:
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return build_strix_agent(
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name=name,
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skills=skills,
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is_root=False,
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scan_mode=scan_mode,
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is_whitebox=is_whitebox,
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interactive=interactive,
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system_prompt_context=system_prompt_context,
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)
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return _factory
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