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50 lines
1.9 KiB
Python
50 lines
1.9 KiB
Python
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"""Repo-bundled analyzer skills, served to the agent as virtual files.
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The two analyzer playbooks live as ``SKILL.md`` files under ``agent/skills/``.
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They are surfaced to the deepagents ``SkillsMiddleware`` via a ``StateBackend``
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mounted at ``/skills/`` in a ``CompositeBackend`` — so the agent reads them with
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``read_file`` without anything ever being written to the execution sandbox.
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The ``files`` channel is seeded at invoke time (see the launchers). Because
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``CompositeBackend`` strips the ``/skills/`` route prefix before delegating to the
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``StateBackend``, the seeded keys are the *stripped* paths (e.g.
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``/bootstrap-repo-analysis/SKILL.md``), while the agent and ``SkillsMiddleware``
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address them under ``/skills/...``.
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"""
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from __future__ import annotations
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from pathlib import Path
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from typing import Any
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from deepagents.backends.utils import create_file_data
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SKILLS_DIR = Path(__file__).resolve().parent.parent / "skills"
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SKILLS_ROUTE = "/skills/"
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BOOTSTRAP_SKILL = "bootstrap-repo-analysis"
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CONTINUAL_SKILL = "continual-learning"
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ANALYZER_MODES = {"bootstrap": BOOTSTRAP_SKILL, "continual": CONTINUAL_SKILL}
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def skill_path_for_mode(mode: str) -> str:
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"""Return the agent-facing ``/skills/<name>/SKILL.md`` path for a run mode."""
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skill = ANALYZER_MODES.get(mode, BOOTSTRAP_SKILL)
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return f"{SKILLS_ROUTE}{skill}/SKILL.md"
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def build_skill_files() -> dict[str, Any]:
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"""Return ``{stripped_path: FileData}`` for every bundled analyzer skill.
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Seed this into the run input's ``files`` so the ``/skills/`` StateBackend route
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can serve them. Keys omit the ``/skills`` prefix (stripped by the composite
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route); values are ``FileData`` v2 entries.
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"""
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files: dict[str, Any] = {}
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for skill in ANALYZER_MODES.values():
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skill_md = SKILLS_DIR / skill / "SKILL.md"
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text = skill_md.read_text(encoding="utf-8")
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files[f"/{skill}/SKILL.md"] = create_file_data(text)
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return files
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