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+#!/usr/bin/env python3
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+"""
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+自动检查生成的SKILL.md是否通过Phase 4质量标准。
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+对照通过标准表格逐项检查，输出通过/不通过和具体原因。
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+
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+用法:
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+ python3 quality_check.py <SKILL.md路径>
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+
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+示例:
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+ python3 quality_check.py .claude/skills/elon-musk-perspective/SKILL.md
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+"""
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+
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+import sys
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+import re
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+from pathlib import Path
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+
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+
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+def check_mental_models(content: str) -> tuple[bool, str]:
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+ """检查心智模型数量（3-7个）"""
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+ # 匹配 ### 模型N: 或 ### N. 等模式
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+ models = re.findall(r'^###\s+(?:模型|Model|心智模型)\s*\d', content, re.MULTILINE)
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+ if not models:
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+ # fallback: 数「### 」开头的行在心智模型section中
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+ in_section = False
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+ count = 0
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+ for line in content.split('\n'):
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+ if re.match(r'^##\s+.*心智模型|Mental Model', line, re.IGNORECASE):
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+ in_section = True
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+ continue
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+ if in_section and re.match(r'^##\s+', line) and '心智模型' not in line:
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+ break
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+ if in_section and re.match(r'^###\s+', line):
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+ count += 1
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+ if count > 0:
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+ passed = 3 <= count <= 7
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+ return passed, f"{count}个心智模型 {'✅' if passed else '❌ (应为3-7个)'}"
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+
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+ count = len(models)
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+ if count == 0:
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+ return False, "未检测到心智模型section"
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+ passed = 3 <= count <= 7
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+ return passed, f"{count}个心智模型 {'✅' if passed else '❌ (应为3-7个)'}"
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+
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+
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+def check_limitations(content: str) -> tuple[bool, str]:
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+ """检查每个模型是否有局限性"""
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+ has_limitation = bool(re.search(r'局限|失效|不适用|盲区|limitation|blind spot', content, re.IGNORECASE))
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+ return has_limitation, "有局限性标注 ✅" if has_limitation else "❌ 未找到局限性描述"
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+
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+
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+def check_expression_dna(content: str) -> tuple[bool, str]:
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+ """检查表达DNA辨识度"""
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+ dna_section = bool(re.search(r'表达DNA|Expression DNA|表达风格', content, re.IGNORECASE))
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+ if not dna_section:
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+ return False, "❌ 未找到表达DNA section"
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+
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+ # 检查是否有具体的风格描述（句式、词汇等）
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+ style_markers = len(re.findall(r'句式|词汇|语气|幽默|节奏|确定性|引用|口头禅', content))
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+ passed = style_markers >= 3
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+ return passed, f"表达DNA特征: {style_markers}项 {'✅' if passed else '❌ (应≥3项)'}"
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+
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+
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+def check_honest_boundary(content: str) -> tuple[bool, str]:
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+ """检查诚实边界（至少3条）"""
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+ # 找诚实边界section
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+ boundary_match = re.search(r'(?:##\s+.*诚实边界|## Honest Boundary)(.*?)(?=\n##\s|\Z)', content, re.DOTALL | re.IGNORECASE)
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+ if not boundary_match:
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+ return False, "❌ 未找到诚实边界section"
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+
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+ boundary_text = boundary_match.group(1)
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+ # 计算列表项
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+ items = re.findall(r'^[-*]\s+', boundary_text, re.MULTILINE)
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+ count = len(items)
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+ passed = count >= 3
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+ return passed, f"诚实边界: {count}条 {'✅' if passed else '❌ (应≥3条)'}"
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+
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+
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+def check_tensions(content: str) -> tuple[bool, str]:
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+ """检查内在张力（至少2对）"""
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+ tension_markers = len(re.findall(r'张力|矛盾|tension|paradox|一方面.*另一方面|既.*又', content, re.IGNORECASE))
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+ passed = tension_markers >= 2
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+ return passed, f"内在张力: {tension_markers}处 {'✅' if passed else '❌ (应≥2处)'}"
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+
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+
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+def check_primary_sources(content: str) -> tuple[bool, str]:
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+ """检查一手来源占比"""
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+ # 找调研来源section
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+ source_section = re.search(r'(?:##\s+.*来源|## Source|## Reference)(.*?)(?=\n##\s|\Z)', content, re.DOTALL | re.IGNORECASE)
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+ if not source_section:
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+ return True, "未找到来源section（跳过检查）"
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+
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+ source_text = source_section.group(1)
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+ primary = len(re.findall(r'一手|primary|本人著作|原始', source_text, re.IGNORECASE))
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+ secondary = len(re.findall(r'二手|secondary|转述|评论', source_text, re.IGNORECASE))
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+ total = primary + secondary
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+ if total == 0:
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+ return True, "未标记来源类型（跳过检查）"
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+
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+ ratio = primary / total
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+ passed = ratio > 0.5
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+ return passed, f"一手来源占比: {primary}/{total} ({ratio:.0%}) {'✅' if passed else '❌ (应>50%)'}"
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+
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+
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+def main():
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+ if len(sys.argv) < 2:
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+ print("用法: python3 quality_check.py <SKILL.md路径>")
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+ sys.exit(1)
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+
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+ skill_path = Path(sys.argv[1])
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+ if not skill_path.exists():
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+ print(f"❌ 文件不存在: {skill_path}")
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+ sys.exit(1)
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+
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+ content = skill_path.read_text(encoding='utf-8')
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+
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+ checks = [
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+ ("心智模型数量", check_mental_models),
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+ ("模型局限性", check_limitations),
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+ ("表达DNA辨识度", check_expression_dna),
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+ ("诚实边界", check_honest_boundary),
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+ ("内在张力", check_tensions),
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+ ("一手来源占比", check_primary_sources),
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+ ]
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+
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+ print(f"质量检查: {skill_path.name}")
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+ print("=" * 50)
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+
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+ passed_count = 0
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+ total = len(checks)
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+
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+ for name, check_fn in checks:
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+ passed, detail = check_fn(content)
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+ status = "✅ PASS" if passed else "❌ FAIL"
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+ print(f" {name:<12} {status} {detail}")
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+ if passed:
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+ passed_count += 1
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+
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+ print("=" * 50)
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+ print(f"结果: {passed_count}/{total} 通过")
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+
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+ if passed_count == total:
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+ print("🎉 全部通过，可以交付")
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+ elif passed_count >= total - 1:
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+ print("⚠️ 基本通过，建议修复不通过项后交付")
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+ else:
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+ print("❌ 多项不通过，建议回到Phase 2迭代")
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+
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+ sys.exit(0 if passed_count == total else 1)
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+
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+
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+if __name__ == '__main__':
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+ main()
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alchain