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/tests/test_optimization_target_position.py

@@ -0,0 +1,29 @@
+"""Characterization tests for optimization context anchoring."""
+
+from app.optimization_flow import OptimizationFlowMixin
+
+
+def test_context_carries_target_position_and_major():
+    session = {
+        "profile": {
+            "job_type": "校招",
+            "target_position": "数据分析师",
+            "anchor": {"major": "统计学"},
+        }
+    }
+    section = {"kind": "internship_experience"}
+
+    context = OptimizationFlowMixin._context(session, section, None)
+
+    assert context["target_position"] == "数据分析师"
+    assert context["major"] == "统计学"
+    assert context["entry_type"] == "internship_experience"
+
+
+def test_context_tolerates_missing_target_position():
+    session = {"profile": {"job_type": "社招", "anchor": {}}}
+    section = {"kind": "work_experience"}
+
+    context = OptimizationFlowMixin._context(session, section, None)
+
+    assert context["target_position"] is None