feat: builder 简历生成 + 轻度优化 + 简历导入交付副本

自内部仓库剥离深度优化与 RAG 知识库后的交付版本：
- Builder 对话式简历生成（FSM + 意图路由 LLM 兜底增强）
- 条目级轻度优化：事实覆盖门禁 + STAR/bullet 修复链，功能/简介/成果与技术栈同级保护
- 简历导入：DOCX/PDF 解析、结构归一、手机号脱敏
- PostgreSQL 运行时 + Alembic 迁移链

Co-Authored-By: Claude <noreply@anthropic.com>

backend/app/resume_skill_advisor.py

@@ -0,0 +1,58 @@
+"""Candidate-only skill recommendations for the resume preview editor."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from .skill_classifier import classify_skills
+from .skill_suggester import SkillSuggester
+
+
+def recommend_skill_candidates(
+    profile: dict[str, Any],
+    existing_skills: list[str],
+    question: str,
+    suggester: SkillSuggester,
+) -> list[dict[str, Any]]:
+    """Return suggestions only; callers must never write them into the resume automatically."""
+    working_profile = dict(profile)
+    tags = dict(working_profile.get("tags") or {})
+    tags["skills"] = existing_skills
+    working_profile["tags"] = tags
+    suggestions = suggester.suggest(working_profile)
+    source_text = _profile_text(working_profile).casefold()
+    target = str(working_profile.get("target_position") or "目标岗位").strip()
+    candidates: list[dict[str, Any]] = []
+    for skill in suggestions:
+        clean = str(skill).strip()
+        if not clean:
+            continue
+        group = classify_skills([clean])
+        category = str(group[0]["category"]) if group else "其他技能"
+        supported = clean.casefold() in source_text
+        reason = (
+            "已在你填写的经历中出现，可作为已掌握技能确认。"
+            if supported
+            else f"与{target}及你的提问“{question.strip()}”相关，作为待学习或待确认技能建议。"
+        )
+        candidates.append({
+            "skill": clean,
+            "category": category,
+            "reason": reason[:160],
+            "evidence_supported": supported,
+        })
+    return candidates[:12]
+
+
+def _profile_text(profile: dict[str, Any]) -> str:
+    values: list[str] = []
+    entries: list[Any] = [profile.get("anchor")]
+    entries.extend(profile.get("experiences") or [])
+    for records in (profile.get("records") or {}).values():
+        entries.extend(records or [])
+    for entry in entries:
+        if not isinstance(entry, dict):
+            continue
+        values.append(str(entry.get("description") or ""))
+        values.extend(str(item) for item in entry.get("highlights") or [] if item)
+    return "\n".join(values)