dev
b96f38276f
Adds the unified_review MCP prompt (invoked as /code-review-graph:unified_review) that drives the unified-review workflow: graph context -> detect_changes -> score_review -> findings -> dedupe_findings -> generate_report. READ-ONLY: every finding waits for a manual fix decision. Takes base and tier (fast/standard/strict) arguments. - prompts.py: unified_review_prompt + docstring count 5->6 - main.py: @mcp.prompt() registration - tests/test_prompts.py: TestUnifiedReviewPrompt + preamble test - docs: LLM-OPTIMIZED-REFERENCE, COMMANDS, CLAUDE.md, INDEX, architecture, README + 4 localized READMEs; tool count 30->31 and prompt count 5->6 synced (historical ROADMAP/FEATURES version notes left unchanged)
16 lines
1.1 KiB
Markdown
16 lines
1.1 KiB
Markdown
# Documentation Index
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- [USAGE.md](USAGE.md) -- How to install and use
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- [FAQ.md](FAQ.md) -- How it compares to LSP, RAG, grep, and similar tools; when not to use it
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- [FEATURES.md](FEATURES.md) -- What's included, changelog
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- [COMMANDS.md](COMMANDS.md) -- All 31 MCP tools, 6 MCP prompts, skills, and CLI commands
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- [GITHUB_ACTION.md](GITHUB_ACTION.md) -- Risk-scored PR review comments via GitHub Actions
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- [CUSTOM_LANGUAGES.md](CUSTOM_LANGUAGES.md) -- Bring your own language via `.code-review-graph/languages.toml`
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- [LLM-OPTIMIZED-REFERENCE.md](../code_review_graph/docs/LLM-OPTIMIZED-REFERENCE.md) -- Token-optimized reference for MCP-capable AI coding agents
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- [architecture.md](architecture.md) -- System design and data flow
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- [schema.md](schema.md) -- Graph node/edge schema, SQLite tables (including flows, communities, FTS5)
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- [TROUBLESHOOTING.md](TROUBLESHOOTING.md) -- Common issues and fixes (including Windows/WSL)
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- [REPRODUCING.md](REPRODUCING.md) -- Reproducing every benchmark number (pinned SHAs, seeded runs, tokenizer calibration)
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- [ROADMAP.md](ROADMAP.md) -- Shipped and planned features
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- [LEGAL.md](LEGAL.md) -- License and privacy
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