86 lines
2.6 KiB
Python
86 lines
2.6 KiB
Python
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from __future__ import annotations
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import re
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Any, Dict, Iterable, List, Optional
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import yaml
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@dataclass(slots=True)
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class Skill:
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name: str
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description: str
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path: Path
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content: str
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metadata: Dict[str, Any] = field(default_factory=dict)
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def summary(self) -> Dict[str, str]:
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return {
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"name": self.name,
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"description": self.description,
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"path": str(self.path),
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}
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class SkillStore:
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"""Loads skills from one or more directories using SKILL.md frontmatter."""
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def __init__(self, roots: Iterable[str | Path]) -> None:
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self.roots = [Path(root).resolve() for root in roots]
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def list_skills(self) -> List[Dict[str, str]]:
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return [skill.summary() for skill in self._discover()]
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def load_skill(self, name: str) -> Skill:
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normalized = name.strip().lower()
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for skill in self._discover():
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if skill.name.lower() == normalized:
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return skill
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raise KeyError(f"Skill not found: {name}")
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def build_prompt_fragment(self, active_skills: Iterable[str]) -> str:
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chunks: List[str] = []
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for skill_name in active_skills:
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skill = self.load_skill(skill_name)
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chunks.append(f"## Skill: {skill.name}\n{skill.content.strip()}")
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return "\n\n".join(chunks)
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def _discover(self) -> List[Skill]:
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skills: List[Skill] = []
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for root in self.roots:
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if not root.exists():
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continue
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for path in sorted(root.rglob("SKILL.md")):
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parsed = self._parse_skill(path)
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if parsed:
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skills.append(parsed)
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return skills
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def _parse_skill(self, path: Path) -> Optional[Skill]:
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raw = path.read_text(encoding="utf-8")
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frontmatter, body = _split_frontmatter(raw)
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data = yaml.safe_load(frontmatter) if frontmatter else {}
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if not isinstance(data, dict):
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data = {}
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name = str(data.get("name") or path.parent.name).strip()
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description = str(data.get("description") or "").strip()
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return Skill(
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name=name,
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description=description,
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path=path,
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content=body.strip(),
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metadata=data,
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)
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_FRONTMATTER_RE = re.compile(r"^---\s*\n(.*?)\n---\s*\n?(.*)$", re.DOTALL)
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def _split_frontmatter(raw: str) -> tuple[str, str]:
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match = _FRONTMATTER_RE.match(raw)
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if not match:
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return "", raw
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return match.group(1), match.group(2)
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