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0xallam
a9982e624c
Main's load_skill tool was deleted during the SDK migration along with the prompt-mutation pattern it relied on. Re-add the capability without the mutation: load_skill(skills=[...]) now returns the skill markdown bodies as a tool result, so the content lands in conversation history as in-context reference rather than as patched-in system prompt content. Same source of truth (load_skills + skill files), same validation (validate_requested_skills) as create_agent. Tool result format is plain markdown (## Skill: <name> headers joined with ---), not the <specialized_knowledge> XML wrapping used at agent-build time. The XML framing was deliberately reserved for prompt-level privileged context; tool-loaded skills are honestly labelled as just-fetched reference material. Close the discovery loop by surfacing the full skill catalog in the system prompt. Without it the model could only guess skill names — discovering them via validation errors on misses. Now every agent sees a categorised <available_skills> block right after the <specialized_knowledge> block with a short hint pointing at create_agent / load_skill. Skills module: factored _iter_user_skill_files() so get_all_skill_names (set, for validation) and get_available_skills (dict by category, for the prompt) share one source of truth on what counts as user-selectable. Internal categories (scan_modes, coordination) stay excluded from both.
37 lines
1.4 KiB
Python
37 lines
1.4 KiB
Python
"""``load_skill`` — fetch skill reference material into the conversation."""
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from __future__ import annotations
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from agents import RunContextWrapper, function_tool
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from strix.skills import load_skills, validate_requested_skills
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@function_tool(timeout=10)
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async def load_skill(ctx: RunContextWrapper, skills: list[str]) -> str:
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"""Return the markdown body of one or more skills as reference material.
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Use this when you need exact syntax / workflow / payload guidance
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right before acting on a technology that wasn't preloaded for your
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agent. The skill content lands inline as a tool result — no
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permanent prompt change, just in-conversation reference.
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For permanent skill assignment, pass ``skills=[…]`` to
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``create_agent`` when spawning a specialist child instead.
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Args:
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skills: List of skill names (e.g. ``["xss", "sql_injection"]``).
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Max 5. Names match the bare files under
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``strix/skills/<category>/<name>.md``.
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"""
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del ctx
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requested = list(skills or [])
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err = validate_requested_skills(requested)
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if err:
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return f"load_skill: {err}"
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contents = load_skills(requested)
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if not contents:
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return "load_skill: no content loaded for requested skills."
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sections = [f"## Skill: {name}\n\n{body}" for name, body in contents.items()]
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return "\n\n---\n\n".join(sections)
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