Initial commit

skills/jd-resume-tailor/scripts/jd_gap.py

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+#!/usr/bin/env python3
+"""
+jd_gap.py — 把 parse_jd.py 的 JSON 与简历文本做 gap 分析
+
+用法：
+    python jd_gap.py --jd jd_parsed.json --resume resume.md --out gap.md
+
+输出 markdown 报告：完美命中 / 隐性命中 / 真缺口 三类，附改写建议。
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import re
+import sys
+from pathlib import Path
+
+
+def load_resume_text(path: Path) -> str:
+    suffix = path.suffix.lower()
+    if suffix in {".md", ".txt"}:
+        return path.read_text(encoding="utf-8")
+    if suffix == ".docx":
+        try:
+            from docx import Document
+        except ImportError:
+            print(
+                "✗ 缺少 python-docx：pip install python-docx --break-system-packages",
+                file=sys.stderr,
+            )
+            sys.exit(1)
+        doc = Document(str(path))
+        return "\n".join(p.text for p in doc.paragraphs)
+    print(f"✗ 暂不支持的格式：{suffix}", file=sys.stderr)
+    sys.exit(1)
+
+
+def find_evidence(resume_text: str, keyword: str, window: int = 30) -> str | None:
+    """在简历里找关键词，返回上下文片段；找不到返回 None。"""
+    pattern = re.escape(keyword)
+    m = re.search(pattern, resume_text, flags=re.IGNORECASE)
+    if not m:
+        return None
+    start = max(0, m.start() - window)
+    end = min(len(resume_text), m.end() + window)
+    snippet = resume_text[start:end].replace("\n", " ").strip()
+    return snippet
+
+
+def fuzzy_hit(resume_text: str, keyword: str) -> str | None:
+    """模糊命中：取关键词的中文 / 英文核心，做包含匹配。"""
+    # 拿前 2 个字 / 前 5 个字符
+    candidates = []
+    if re.search(r"[一-龥]", keyword):
+        if len(keyword) >= 4:
+            candidates.append(keyword[:2])
+            candidates.append(keyword[-2:])
+    else:
+        if len(keyword) >= 4:
+            candidates.append(keyword[:4].lower())
+    text_low = resume_text.lower()
+    for c in candidates:
+        if c and c in text_low:
+            return c
+    return None
+
+
+def analyze(jd: dict, resume_text: str) -> dict:
+    perfect, implicit, missing = [], [], []
+
+    # 用 must_have 句子里抽出来的 skills 作为对比项
+    candidates = jd.get("skills_extracted", []) + jd.get("must_have", [])
+
+    seen = set()
+    for c in candidates:
+        # 句子层面太长，截短
+        keyword = c.strip()
+        if len(keyword) > 30:
+            # 从长句子里抽更短的关键词
+            short_tokens = re.findall(
+                r"[A-Za-z][A-Za-z0-9+/.\-_]{1,20}|[一-龥]{2,6}",
+                keyword,
+            )
+            for t in short_tokens:
+                if t.lower() not in seen:
+                    seen.add(t.lower())
+                    process_one(t, resume_text, perfect, implicit, missing)
+        else:
+            if keyword.lower() not in seen:
+                seen.add(keyword.lower())
+                process_one(keyword, resume_text, perfect, implicit, missing)
+
+    return {"perfect": perfect, "implicit": implicit, "missing": missing}
+
+
+def process_one(keyword, resume_text, perfect, implicit, missing):
+    ev = find_evidence(resume_text, keyword)
+    if ev:
+        perfect.append({"keyword": keyword, "evidence": ev})
+        return
+    fuzzy = fuzzy_hit(resume_text, keyword)
+    if fuzzy:
+        implicit.append({"keyword": keyword, "fuzzy_match": fuzzy})
+    else:
+        missing.append(keyword)
+
+
+def render(jd: dict, gap: dict) -> str:
+    lines = ["# JD ⇄ Resume Gap 分析报告", ""]
+
+    spec = jd.get("special_requirements", {})
+    if spec:
+        lines += ["## JD 硬条件", ""]
+        for k, v in spec.items():
+            lines.append(f"- **{k}**：{v}")
+        lines.append("")
+
+    lines += ["## ✅ 完美命中（简历里有明确证据）", ""]
+    if gap["perfect"]:
+        for item in gap["perfect"][:30]:
+            lines.append(f"- **{item['keyword']}** —— 证据：`...{item['evidence']}...`")
+    else:
+        lines.append("（无）")
+    lines.append("")
+
+    lines += ["## 🟡 隐性命中（简历里有近似但用词不同，建议改写时对齐）", ""]
+    if gap["implicit"]:
+        for item in gap["implicit"][:20]:
+            lines.append(f"- **JD 关键词：{item['keyword']}**（简历里出现：`{item['fuzzy_match']}`）")
+    else:
+        lines.append("（无）")
+    lines.append("")
+
+    lines += ["## 🔴 真缺口（简历完全没有，需要确认 / 补充 / 转换叙事）", ""]
+    if gap["missing"]:
+        for kw in gap["missing"][:30]:
+            lines.append(f"- **{kw}**")
+    else:
+        lines.append("（无）")
+    lines.append("")
+
+    lines += [
+        "---",
+        "## 改写建议",
+        "",
+        "1. **完美命中** 的部分保留，但确保措辞与 JD 一致（比如 JD 用『A/B 测试』就别写『AB 实验』）",
+        "2. **隐性命中** 是性价比最高的优化点 —— 把简历里的近义词改成 JD 的措辞",
+        "3. **真缺口** 分两类：",
+        "   - 你做过但没写？→ 补到对应经历的 bullet 里",
+        "   - 你没做过？→ **不要编造**。可以在 cover letter / Summary 里诚实说明 transferable skill",
+        "4. 把改后的简历再跑一次 ats_check.py 看命中率是否提升",
+    ]
+    return "\n".join(lines)
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--jd", required=True, help="parse_jd.py 输出的 json")
+    parser.add_argument("--resume", required=True, help="简历文件 (.md/.txt/.docx)")
+    parser.add_argument("--out", help="输出 markdown 路径")
+    args = parser.parse_args()
+
+    jd = json.loads(Path(args.jd).read_text(encoding="utf-8"))
+    resume_text = load_resume_text(Path(args.resume))
+    gap = analyze(jd, resume_text)
+    report = render(jd, gap)
+
+    if args.out:
+        Path(args.out).write_text(report, encoding="utf-8")
+        print(f"✓ Gap 报告已生成：{args.out}")
+    else:
+        print(report)
+
+
+if __name__ == "__main__":
+    main()