Files
code-review-graph/.opencode/command/code-review-graph-project-review.md
T
dev 307d2fd471 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
2026-08-06 13:56:54 +08:00

2.3 KiB

description, agent
description agent
Whole-project or single-feature code review (not diff-based) using graph-wide analysis and objective scoring. build

Project Review

Review the entire codebase or a single feature/module, independent of the git diff. The scope is driven by your instruction.

$ARGUMENTS

Token optimization: Before starting, call get_docs_section_tool(section_name="project-review") for the optimized workflow.

Steps

  1. Parse the scope from the user instruction:

    • "对项目代码进行全面审查" / "全面审查" / "整个项目" → scope=whole-project
    • "审查 <功能/模块> 的代码" (e.g. payment, auth) → scope=feature, target=
  2. Ensure the graph is current by calling build_or_update_graph_tool().

  3. Map the architecture by calling get_architecture_overview_tool(detail_level="minimal") and list_communities_tool(detail_level="minimal").

  4. Scan high-risk areas (whole-project): get_knowledge_gaps_tool(), get_hub_nodes_tool(), get_bridge_nodes_tool(), find_large_functions_tool(), get_surprising_connections_tool().

  5. Score objectively:

    • whole-project: score_review_tool(all_files=True) — every source file in the graph
    • feature: semantic_search_nodes_tool(query=<target>) + query_graph_tool(pattern="children_of", target=<target>) to locate files, then score_review_tool(changed_files=<files>) + get_impact_radius_tool(changed_files=<files>)
  6. Review the code (Layer 1 chain decomposition): eight categories + gstack CRITICAL sub-pass. Produce findings with severity (blocker/major/minor), confidence (1-10), file:line, and proposed fix.

  7. Merge findings by calling dedupe_findings_tool(findings=<your findings>).

  8. Generate the report by calling generate_report_tool(review_data=<verdict, scope, metrics, merged findings>) — writes code-review-report.html and code-review-report.md (default format="both").

  9. Report the verdict ( PASS / FAIL), severity counts, each issue with confidence + fix, and manual-review items.

Important Rules

  • READ-ONLY. This workflow never modifies code, commits, or pushes. Every finding waits for a manual fix decision.
  • Any blocker → verdict FAIL, regardless of other scores.
  • This is not a diff review. For diff-based review use /code-review-graph-unified-review.