yaojingang
252 lines
9.4 KiB
Python
252 lines
9.4 KiB
Python
#!/usr/bin/env python3
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import argparse
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import json
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from pathlib import Path
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try:
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import yaml
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except ImportError: # pragma: no cover
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yaml = None
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def parse_frontmatter(text: str) -> tuple[dict, str]:
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lines = text.splitlines()
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if not lines or lines[0].strip() != "---":
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return {}, text
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try:
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end_index = lines[1:].index("---") + 1
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except ValueError:
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return {}, text
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frontmatter = "\n".join(lines[1:end_index])
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body = "\n".join(lines[end_index + 1 :]).lstrip()
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if yaml is not None:
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payload = yaml.safe_load(frontmatter) or {}
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return payload if isinstance(payload, dict) else {}, body
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data = {}
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for line in frontmatter.splitlines():
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if ":" not in line:
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continue
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key, value = line.split(":", 1)
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data[key.strip()] = value.strip().strip('"')
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return data, body
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def extract_title(body: str, fallback: str) -> str:
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for line in body.splitlines():
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if line.startswith("# "):
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return line[2:].strip()
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return fallback
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def parse_reference(value: str, source: str) -> dict:
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parts = [part.strip() for part in value.split("::")]
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while len(parts) < 4:
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parts.append("")
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name, category, borrow, avoid = parts[:4]
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return {
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"name": name or "Unnamed reference",
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"category": category or "general",
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"borrow": borrow or "Capture the reusable pattern, not the prose.",
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"avoid": avoid or "Do not copy source-specific language or unnecessary weight.",
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"source": source,
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}
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def infer_scan_focus(skill_dir: Path, description: str) -> list[dict]:
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checks = []
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if (skill_dir / "evals").exists():
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checks.append(
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{
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"label": "Evaluation pattern",
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"reason": "This skill already carries eval assets, so benchmark how top examples define trigger boundaries and quality gates.",
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}
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)
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if (skill_dir / "scripts").exists():
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checks.append(
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{
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"label": "Execution pattern",
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"reason": "There is deterministic logic in scripts, so compare how strong references separate prose from executable steps.",
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}
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)
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if (skill_dir / "agents" / "interface.yaml").exists():
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checks.append(
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{
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"label": "Portability pattern",
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"reason": "The package carries neutral metadata, so scan how good references preserve semantics across targets without forking source.",
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}
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)
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checks.append(
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{
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"label": "Method pattern",
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"reason": f"Use the core job description as the anchor for comparison: {description}",
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}
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)
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return checks[:4]
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def split_references(references: list[dict]) -> tuple[list[dict], list[dict]]:
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externals = [item for item in references if item.get("source") == "external"]
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locals_ = [item for item in references if item.get("source") == "local"]
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return externals, locals_
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def build_summary(skill_dir: Path, references: list[dict]) -> dict:
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skill_text = (skill_dir / "SKILL.md").read_text(encoding="utf-8")
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frontmatter, body = parse_frontmatter(skill_text)
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name = frontmatter.get("name", skill_dir.name)
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description = frontmatter.get("description", "No description found.")
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title = extract_title(body, name.replace("-", " ").title())
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focus = infer_scan_focus(skill_dir, description)
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external_references, local_constraints = split_references(references)
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borrow_plan = [
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"External benchmark first: let world-class references define the upper bound for method, structure, execution, or portability.",
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"Local fit second: use local assets only to detect naming conflicts, private dependencies, or compatibility constraints.",
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"Borrow patterns, not prose: extract loops, boundaries, metadata, and operator flow without copying source-specific language.",
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"Keep the package light: reject any borrowed pattern that increases context cost faster than it increases reliability.",
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]
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if external_references:
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borrow_plan.append("Apply only the benchmark patterns that fit the chosen archetype, gates, and context budget.")
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return {
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"skill_name": name,
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"title": title,
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"description": description,
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"scan_focus": focus,
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"external_references": external_references,
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"local_constraints": local_constraints,
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"borrow_plan": borrow_plan,
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"priority_rule": "External benchmark objects set the pattern ceiling. Local files only calibrate fit, risk, and compatibility.",
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"non_goals": [
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"Do not copy source prose or branding into the new skill.",
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"Do not import gates that cost more context than they save.",
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"Do not use benchmark scanning to justify scope creep.",
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"Do not let local historical habits outrank stronger public benchmarks.",
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],
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}
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def render_markdown(summary: dict) -> str:
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lines = [
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"# Reference Scan",
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"",
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f"Skill: `{summary['skill_name']}`",
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"",
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"## Why This Step Exists",
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"",
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"Use a short benchmark pass before authoring the package in depth. External benchmark objects should define the pattern ceiling. Local files are used afterward only to calibrate fit, privacy, naming, and compatibility.",
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"",
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"## Current Skill Anchor",
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"",
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f"- Title: `{summary['title']}`",
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f"- Description: {summary['description']}",
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"",
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"## Scan Focus",
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"",
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]
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for item in summary["scan_focus"]:
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lines.append(f"- **{item['label']}**: {item['reason']}")
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lines.extend(["", "## Priority Rule", "", f"- {summary['priority_rule']}", ""])
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lines.extend(["## External Benchmark Objects", ""])
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if summary["external_references"]:
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for ref in summary["external_references"]:
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lines.extend(
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[
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f"### {ref['name']}",
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f"- Category: `{ref['category']}`",
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f"- Borrow: {ref['borrow']}",
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f"- Avoid: {ref['avoid']}",
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"",
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]
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)
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else:
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lines.extend(
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[
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"- No explicit external benchmark objects recorded yet.",
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"- Recommended: capture 2 to 5 external references at most.",
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"- Suggested mix: one method reference, one structure reference, one execution or portability reference.",
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"",
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]
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)
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lines.extend(["## Local Fit Check", ""])
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if summary["local_constraints"]:
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for ref in summary["local_constraints"]:
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lines.extend(
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[
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f"### {ref['name']}",
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f"- Category: `{ref['category']}`",
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f"- Keep in mind: {ref['borrow']}",
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f"- Do not inherit: {ref['avoid']}",
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"",
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]
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)
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else:
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lines.extend(
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[
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"- No local constraints recorded yet.",
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"- Use this section for naming collisions, private dependencies, compatibility limits, or existing library conventions.",
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"",
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]
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)
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lines.extend(["## Borrow Plan", ""])
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for item in summary["borrow_plan"]:
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lines.append(f"- {item}")
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lines.extend(["", "## Non-Goals", ""])
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for item in summary["non_goals"]:
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lines.append(f"- {item}")
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return "\n".join(lines).strip() + "\n"
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def render_reference_scan(skill_dir: Path, references: list[dict], output_md: Path | None = None, output_json: Path | None = None) -> dict:
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skill_dir = skill_dir.resolve()
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reports_dir = skill_dir / "reports"
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reports_dir.mkdir(parents=True, exist_ok=True)
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output_md = output_md or reports_dir / "reference-scan.md"
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output_json = output_json or reports_dir / "reference-scan.json"
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summary = build_summary(skill_dir, references)
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output_md.write_text(render_markdown(summary), encoding="utf-8")
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output_json.write_text(json.dumps(summary, ensure_ascii=False, indent=2), encoding="utf-8")
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return {
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"ok": True,
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"skill_dir": str(skill_dir),
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"artifacts": {
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"markdown": str(output_md),
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"json": str(output_json),
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},
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"summary": summary,
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}
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def main() -> None:
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parser = argparse.ArgumentParser(description="Render a benchmark-oriented reference scan for a skill package.")
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parser.add_argument("skill_dir", nargs="?", default=".")
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parser.add_argument("--external-reference", action="append", default=[], help="Format: name::category::borrow::avoid")
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parser.add_argument("--local-constraint", action="append", default=[], help="Format: name::category::borrow::avoid")
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parser.add_argument("--reference", action="append", default=[], help="Legacy alias for --external-reference.")
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parser.add_argument("--output-md")
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parser.add_argument("--output-json")
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args = parser.parse_args()
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refs = [parse_reference(item, "external") for item in [*args.external_reference, *args.reference]]
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refs.extend(parse_reference(item, "local") for item in args.local_constraint)
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result = render_reference_scan(
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Path(args.skill_dir),
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refs,
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Path(args.output_md).resolve() if args.output_md else None,
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Path(args.output_json).resolve() if args.output_json else None,
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)
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print(json.dumps(result, ensure_ascii=False, indent=2))
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if __name__ == "__main__":
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main()
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