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
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@@ -1,6 +1,6 @@
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"""MCP prompt templates for Code Review Graph.
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Provides 6 pre-built prompt workflows, all enforcing token-efficient
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Provides 7 pre-built prompt workflows, all enforcing token-efficient
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detail_level="minimal" first patterns with get_minimal_context entry point.
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1. review_changes - pre-commit review using detect_changes + affected_flows
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@@ -9,6 +9,7 @@ detail_level="minimal" first patterns with get_minimal_context entry point.
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4. onboard_developer - new dev orientation using stats, architecture, flows
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5. pre_merge_check - PR readiness with risk scoring, test gaps, dead code
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6. unified_review - three-layer review: graph context + scoring + dedupe + report
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7. project_review - whole-project or single-feature review (not diff-based)
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"""
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from __future__ import annotations
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@@ -209,9 +210,91 @@ def unified_review_prompt(
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'6. Call `dedupe_findings(findings=<your findings>)` to merge '
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"by fingerprint, boost multi-source confidence and compute the "
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"PR quality score.\n"
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'7. Call `generate_report(review_data=<verdict, tier, scope, '
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'metrics, merged findings>)` to write code-review-report.html.\n'
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"8. Output: verdict (✅ PASS / ❌ FAIL), severity counts, each "
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"issue with confidence + fix, and the manual-review items. "
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"Any blocker → verdict ❌ FAIL."
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'7. Call `generate_report(review_data=<verdict, tier, scope, '
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'metrics, merged findings>)` to write code-review-report.html '
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"and code-review-report.md (format=\"both\").\n"
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"8. Output: verdict (✅ PASS / ❌ FAIL), severity counts, each "
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"issue with confidence + fix, and the manual-review items. "
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"Any blocker → verdict ❌ FAIL."
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)
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def project_review_prompt(
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scope: str = "whole-project",
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target: str = "",
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) -> list[Message]:
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"""Whole-project or single-feature code review workflow (not diff-based).
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Reviews the entire codebase (``scope="whole-project"``) or a single
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feature/module/function (``scope="feature"`` with ``target``), using
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graph-wide analysis and objective scoring independent of the git diff.
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READ-ONLY: every finding waits for a manual fix decision.
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Args:
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scope: ``whole-project`` reviews every source file in the graph;
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``feature`` reviews only the code related to ``target``.
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target: Feature/module/function keyword when ``scope="feature"``
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(e.g. "payment", "auth", "checkout flow").
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"""
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scope_note = (
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"whole-project scope: score every source file with "
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"`score_review(all_files=True)`."
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if scope == "whole-project"
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else (
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"feature scope: locate the target's files with semantic search "
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"and graph queries, then score only those files."
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)
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)
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common = (
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f"## Project Review Workflow (scope={scope}, target={target})\n"
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f"{scope_note}\n"
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"**READ-ONLY.** Present every finding for a manual fix decision. "
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"Never modify code, commit, or push.\n"
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'1. Call `get_minimal_context(task="project review")` for graph '
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"stats and community overview.\n"
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'2. Call `build_or_update_graph()` to ensure the graph is current.\n'
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'3. Map the architecture: `get_architecture_overview('
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'detail_level="minimal")` and `list_communities('
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'detail_level="minimal")`.\n'
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'4. Locate high-risk areas: `get_knowledge_gaps()`, '
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'`get_hub_nodes()`, `get_bridge_nodes()`, `find_large_functions()` '
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"and `get_surprising_connections()`.\n"
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)
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if scope == "whole-project":
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workflow = (
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'5. Score every source file: `score_review(all_files=True)`.\n'
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"6. For the top-risk communities, drill in with "
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'`get_community(include_members=True)` and '
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'`query_graph(pattern="children_of", target=<community>)`.\n'
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"7. Produce findings with severity (blocker/major/minor), "
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"confidence (1-10), file:line and a proposed fix.\n"
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"8. Call `dedupe_findings(findings=<your findings>)` to merge "
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"and compute the PR quality score.\n"
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'9. Call `generate_report(review_data=<verdict, scope, '
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'metrics, merged findings>)` (format="both").\n'
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"10. Output the verdict (✅ PASS / ❌ FAIL), severity counts, "
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"each issue, and the manual-review items.\n"
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)
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else:
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workflow = (
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'5. Locate the feature code: `semantic_search_nodes(query='
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'<target>)` and `query_graph(pattern="children_of", '
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'target=<target>)`; collect the related files.\n'
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"6. Map the blast radius: `get_impact_radius(changed_files="
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"<collected files>)`.\n"
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'7. Score the feature: `score_review(changed_files=<files + '
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'impacted files>)`.\n'
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"8. Review the feature code (Layer 1 chain decomposition) and "
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"produce findings with severity, confidence, file:line and a "
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"proposed fix.\n"
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"9. Call `dedupe_findings(findings=<your findings>)` to merge "
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"and compute the PR quality score.\n"
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'10. Call `generate_report(review_data=<verdict, scope, '
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'metrics, merged findings>)` (format="both").\n'
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"11. Output the verdict (✅ PASS / ❌ FAIL), severity counts, "
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"each issue, and the manual-review items.\n"
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)
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return _user(f"{_TOKEN_EFFICIENCY_PREAMBLE}\n{common}{workflow}")
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