add skill_search SOP to tracked memory files

memory/skill_search/skill_search/__main__.py

@@ -0,0 +1,116 @@
+"""CLI 入口: python -m skill_search"""
+from __future__ import annotations
+import argparse, json, sys
+from .engine import SearchResult, SkillSearchError, detect_environment, search, get_stats
+
+
+# ── 格式化 ───────────────────────────────────────────────
+
+def format_results(results: list[SearchResult], env: dict, query: str) -> str:
+    lines = [f'🔍 搜索: "{query}"',
+             f"🖥️  环境: {env.get('os','?')} / {env.get('shell','?')} / {', '.join(env.get('runtimes',[]))}",
+             f"📊 找到 {len(results)} 个匹配结果\n"]
+    if not results:
+        lines.append("未找到匹配的 skill。试试其他关键词？")
+        return "\n".join(lines)
+    for i, r in enumerate(results, 1):
+        s = r.skill
+        safe_icon = "🟢" if s.autonomous_safe else "🔴"
+        score_bar = "█" * int(r.final_score * 10) + "░" * (10 - int(r.final_score * 10))
+        lines += [
+            f"{'─'*60}",
+            f"#{i}  {safe_icon} {s.name}",
+            f"    路径: {s.key}",
+            f"    类别: {s.category} | 标签: {', '.join(s.tags[:5])}",
+            f"    摘要: {s.one_line_summary}",
+            f"    评分: [{score_bar}] {r.final_score:.2f}  (相关={r.relevance:.2f} 质量={r.quality:.1f})",
+            f"    清晰={s.clarity} 完整={s.completeness} 可操作={s.actionability} | 形式={s.form}",
+        ]
+        if r.match_reasons:
+            lines.append(f"    匹配: {' | '.join(r.match_reasons[:3])}")
+        if r.warnings:
+            lines.extend(f"    {w}" for w in r.warnings)
+        lines.append("")
+    lines.append(f"{'─'*60}")
+    return "\n".join(lines)
+
+
+def format_results_json(results: list[SearchResult]) -> list[dict]:
+    out = []
+    for r in results:
+        s = r.skill
+        out.append({
+            "rank": len(out) + 1, "key": s.key, "name": s.name,
+            "category": s.category, "tags": s.tags,
+            "description": s.description, "one_line_summary": s.one_line_summary,
+            "scores": {"final": round(r.final_score, 3), "relevance": round(r.relevance, 3),
+                       "quality": round(r.quality, 1), "clarity": s.clarity,
+                       "completeness": s.completeness, "actionability": s.actionability},
+            "safety": {"autonomous_safe": s.autonomous_safe, "blast_radius": s.blast_radius,
+                       "requires_credentials": s.requires_credentials,
+                       "data_exposure": s.data_exposure, "effect_scope": s.effect_scope},
+            "platform": {"os": s.os, "runtimes": s.runtimes, "tools": s.tools, "services": s.services},
+            "warnings": r.warnings, "match_reasons": r.match_reasons,
+        })
+    return out
+
+
+# ── CLI ──────────────────────────────────────────────────
+
+def main():
+    parser = argparse.ArgumentParser(prog="skill_search",
+        description="Skill 检索系统 — 根据环境和需求智能推荐 skill（API 客户端）")
+    parser.add_argument("query", nargs="?", help="搜索关键词（如: 'python testing'）")
+    parser.add_argument("--category", "-cat", help="限定类别")
+    parser.add_argument("--top", "-k", type=int, default=10, help="返回结果数（默认 10）")
+    parser.add_argument("--json", action="store_true", help="JSON 格式输出")
+    parser.add_argument("--env", action="store_true", help="仅显示检测到的环境信息")
+    parser.add_argument("--stats", action="store_true", help="显示索引统计信息")
+    parser.add_argument("--api-url", help="指定 API 地址（也可用 SKILL_SEARCH_API 环境变量）")
+    args = parser.parse_args()
+
+    if args.api_url:
+        import os; os.environ["SKILL_SEARCH_API"] = args.api_url
+
+    env = detect_environment()
+
+    if args.env:
+        print("🖥️  当前环境:")
+        print(f"  OS:       {env['os']}")
+        print(f"  Shell:    {env['shell']}")
+        print(f"  运行时:   {', '.join(env['runtimes'])}")
+        print(f"  工具:     {', '.join(env['tools'])}")
+        print(f"  模型能力: tool_calling={env['model']['tool_calling']}, "
+              f"reasoning={env['model']['reasoning']}, context={env['model']['context_window']}")
+        return
+
+    if args.stats:
+        try:
+            stats = get_stats(env)
+            print(f"📊 索引统计:")
+            print(f"  总计: {stats.get('total', '?')} 个 skills")
+            print(f"  自动安全: {stats.get('safe_count', '?')} 个")
+            if 'categories' in stats:
+                print(f"  类别分布:")
+                for cat, cnt in sorted(stats['categories'].items(), key=lambda x: -x[1]):
+                    print(f"    {cat:15s} {cnt:4d}")
+        except SkillSearchError as e:
+            print(f"❌ {e}", file=sys.stderr); sys.exit(1)
+        return
+
+    if not args.query:
+        parser.print_help(); return
+
+    try:
+        results = search(query=args.query, env=env, category=args.category, top_k=args.top)
+    except SkillSearchError as e:
+        print(f"❌ {e}", file=sys.stderr); sys.exit(1)
+
+    if args.json:
+        print(json.dumps(format_results_json(results), indent=2, ensure_ascii=False))
+    else:
+        print(format_results(results, env, args.query))
+
+
+if __name__ == "__main__":
+    main()