feat: add project-review workflow (whole-project / single-feature review)

Adds the project-review workflow for code review independent of the git
diff. The scope is parsed from the user instruction: 全面/整个项目 ->
whole-project (score every source file), otherwise feature + target
keyword (locate the code with semantic search + graph queries).

- scoring_tools.py: score_review_func gains all_files=True to score every
  source file in the graph via store.get_all_files()
- main.py: score_review_tool gains all_files param; registers the
  project_review MCP prompt (prompts 6->7)
- prompts.py: project_review_prompt(scope, target) with whole-project and
  feature branches (fixed a precedence bug that truncated the feature text)
- skills.py + skills/project-review/: new read-only project-review skill
  with shared checklists
- .opencode/command/code-review-graph-project-review.md: slash command
- tests: test_project_review.py (prompt rendering), TestProjectReviewPrompt,
  skill count assertions 5->6, all_files wiring checks
- docs: prompts (6->7) + project-review entries across COMMANDS, CLAUDE,
  README (+localized), INDEX, architecture, LLM-OPTIMIZED-REFERENCE,
  CHANGELOG

code_review_graph/scoring.py

@@ -624,6 +624,8 @@ def build_report_data(
         "files": review_data.get("files", ""),
         "baseline": review_data.get("baseline", "generic"),
         "verdict": review_data.get("verdict", "❌ FAIL"),
+        "quality_score": review_data.get("quality_score"),
+        "counts": review_data.get("counts", {}),
         "metrics": {},
         "issues": [],
         "manual_review": review_data.get("manual_review", []),
@@ -656,3 +658,135 @@ def build_report_data(
         })
 
     return data
+
+
+# ---------------------------------------------------------------------------
+# Markdown report rendering (Chinese)
+# ---------------------------------------------------------------------------
+
+#: Human-readable labels for the Chinese Markdown report.
+_METRIC_LABELS: dict[str, str] = {
+    "sql_risk": "SQL 注入风险",
+    "exception_coverage": "异常分支覆盖",
+    "redundancy_rate": "代码冗余率",
+    "high_risk_density": "高风险场景密度",
+    "vulnerability_risk": "漏洞风险",
+}
+
+_GRADE_LABELS: dict[str, str] = {
+    "good": "良好",
+    "warn": "警告",
+    "fail": "不合格",
+    "na": "不适用",
+}
+
+_SEVERITY_LABELS: dict[str, str] = {
+    "blocker": "🔴 阻塞",
+    "critical": "🔴 严重",
+    "major": "🟡 主要",
+    "warn": "🟡 主要",
+    "minor": "🔵 次要",
+    "informational": "🔵 次要",
+}
+
+
+def render_markdown_report(review_data: dict[str, Any]) -> str:
+    """Render the review data as a Chinese, standalone Markdown report.
+
+    Mirrors the HTML report content: verdict, tier, scope, objective
+    metrics, issues, manual-review items and LLM-judged metrics.  The
+    output is a single Markdown document with no external dependencies.
+
+    Args:
+        review_data: Review data dict (see :func:`build_report_data`).
+
+    Returns:
+        The Markdown report text.
+    """
+    data = build_report_data(review_data)
+    lines: list[str] = []
+
+    lines.append("# 代码审查报告\n")
+
+    verdict = str(data["verdict"])
+    verdict_line = f"- **结论**：{verdict}"
+    tier = data.get("tier") or "standard"
+    scope = data.get("scope") or "change-level"
+    baseline = data.get("baseline") or "generic"
+    lines.append(verdict_line)
+    lines.append(
+        f"- **档位**：{tier} · **范围**：{scope} · **基线**：{baseline}"
+    )
+    if data.get("timestamp"):
+        lines.append(f"- **生成时间**：{data['timestamp']}")
+    if data.get("files"):
+        lines.append(f"- **文件**：{data['files']}")
+    qs = data.get("quality_score")
+    if qs is not None:
+        lines.append(f"- **PR 质量分**：{qs}/10")
+    counts = data.get("counts") or {}
+    if counts:
+        lines.append(
+            f"- **问题统计**：{counts.get('critical', 0)} 严重 · "
+            f"{counts.get('informational', 0)} 次要"
+        )
+    lines.append("")
+
+    # Objective metrics
+    metrics = data.get("metrics") or {}
+    if metrics:
+        lines.append("## 客观指标\n")
+        lines.append("| 指标 | 数值 | 评级 | 说明 |")
+        lines.append("|---|---|---|---|")
+        for name, m in metrics.items():
+            label = _METRIC_LABELS.get(name, name)
+            value = m.get("value")
+            value_text = str(value) if value is not None else "N/A"
+            grade = m.get("grade") or "na"
+            grade_text = _GRADE_LABELS.get(grade, grade)
+            note = str(m.get("note", "") or "")
+            note = note.replace("\n", " ")
+            lines.append(f"| {label} | {value_text} | {grade_text} | {note} |")
+        lines.append("")
+
+    # Issues
+    issues = data.get("issues") or []
+    lines.append(f"## 问题清单（{len(issues)}）\n")
+    if not issues:
+        lines.append("未发现问题。\n")
+    for i, issue in enumerate(issues, start=1):
+        sev = str(issue.get("severity") or "minor").lower()
+        sev_label = _SEVERITY_LABELS.get(sev, sev)
+        category = str(issue.get("category") or "")
+        message = str(issue.get("message") or "")
+        location = str(issue.get("location") or "")
+        conf = issue.get("confidence")
+        fix = str(issue.get("fix") or "")
+        lines.append(
+            f"{i}. **{sev_label}** {message}"
+            f"{f'（置信度 {conf}/10）' if conf is not None else ''}"
+        )
+        if category:
+            lines.append(f"   - **类别**：{category}")
+        if location:
+            lines.append(f"   - **位置**：`{location}`")
+        if fix:
+            lines.append(f"   - **修复建议**：{fix}")
+        lines.append("")
+
+    # Manual review
+    manual = data.get("manual_review") or []
+    if manual:
+        lines.append("## 需要人工审查\n")
+        for m in manual:
+            lines.append(f"- {m}")
+        lines.append("")
+
+    # LLM-judged metrics
+    judged = data.get("llm_judged") or []
+    if judged:
+        lines.append("## 需 LLM 判断的指标\n")
+        lines.append(", ".join(str(j) for j in judged))
+        lines.append("")
+
+    return "\n".join(lines).strip() + "\n"