84 lines
2.5 KiB
Python
84 lines
2.5 KiB
Python
# -*- coding: utf-8 -*-
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"""Skill metadata parsing helpers for SKILL.md files."""
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import List
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import yaml
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@dataclass(frozen=True)
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class SkillMetadata:
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"""Parsed metadata for a skill package."""
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skill_name: str
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path: Path
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source: str
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name: str
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description: str
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version: str = ""
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tools: List[str] = field(default_factory=list)
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allowed_tools: List[str] = field(default_factory=list)
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denied_tools: List[str] = field(default_factory=list)
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def parse_skill_metadata(skill_dir: Path, source: str) -> SkillMetadata:
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"""Parse SKILL.md frontmatter with a forgiving schema."""
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skill_name = skill_dir.name
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skill_file = skill_dir / "SKILL.md"
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if not skill_file.exists():
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return SkillMetadata(
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skill_name=skill_name,
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path=skill_dir,
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source=source,
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name=skill_name,
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description="",
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)
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raw = skill_file.read_text(encoding="utf-8").strip()
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frontmatter = {}
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body = raw
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if raw.startswith("---"):
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parts = raw.split("---", 2)
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if len(parts) >= 3:
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try:
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frontmatter = yaml.safe_load(parts[1].strip()) or {}
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except yaml.YAMLError:
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frontmatter = {}
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body = parts[2].strip()
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if not isinstance(frontmatter, dict):
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frontmatter = {}
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description = str(frontmatter.get("description") or "").strip()
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if not description and body:
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description = body.splitlines()[0].strip().lstrip("#").strip()
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return SkillMetadata(
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skill_name=skill_name,
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path=skill_dir,
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source=source,
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name=str(frontmatter.get("name") or skill_name).strip() or skill_name,
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description=description,
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version=str(frontmatter.get("version") or "").strip(),
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tools=_string_list(frontmatter.get("tools")),
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allowed_tools=_string_list(frontmatter.get("allowed_tools")),
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denied_tools=_string_list(frontmatter.get("denied_tools")),
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)
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def _string_list(value) -> List[str]:
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if isinstance(value, str):
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item = value.strip()
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return [item] if item else []
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if not isinstance(value, list):
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return []
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seen: List[str] = []
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for item in value:
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if not isinstance(item, str):
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continue
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normalized = item.strip()
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if normalized and normalized not in seen:
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seen.append(normalized)
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return seen
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