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/review-pr

Review a PR or branch diff using the knowledge graph for full structural context. Outputs a structured review with blast-radius analysis.

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code-review-graph
30k7 skills2 hooks1 MCP
Install
$ npx -y skills add tirth8205/code-review-graph --skill review-pr --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/review-pr

Context preview

The summary Claude sees to decide when to auto-load this skill.

Review a PR or branch diff using the knowledge graph for full structural context. Outputs a structured review with blast-radius analysis.

SKILL.md

review-pr.SKILL.md
name: review-pr
description: Review a PR or branch diff using the knowledge graph for full structural context. Outputs a structured review with blast-radius analysis.
argument-hint: "[PR number or branch name]"

Review PR

Perform a comprehensive code review of a pull request or branch diff using the knowledge graph.

**Token optimization:** Before starting, call `get_docs_section_tool(section_name="review-pr")` for the optimized workflow. Never include full files unless explicitly asked.

Steps

1. **Identify the changes** for the PR:

  • If a PR number or branch is provided, use `git diff main...<branch>` to get changed files
  • Otherwise auto-detect from the current branch vs main/master

2. **Update the graph** by calling `build_or_update_graph_tool(base="main")` to ensure the graph reflects the current state.

3. **Get the full review context** by calling `get_review_context_tool(base="main")`:

  • This uses `main` (or the specified base branch) as the diff base
  • Returns all changed files across all commits in the PR

4. **Analyze impact** by calling `get_impact_radius_tool(base="main")`:

  • Review the blast radius across the entire PR
  • Identify high-risk areas (widely depended-upon code)

5. **Deep-dive each changed file**:

  • Read the full source of files with significant changes
  • Use `query_graph_tool(pattern="callers_of", target=<func>)` for high-risk functions
  • Use `query_graph_tool(pattern="tests_for", target=<func>)` to verify test coverage
  • Check for breaking changes in public APIs

6. **Generate structured review output**:

   ## PR Review: <title>

   ### Summary
   <1-3 sentence overview>

   ### Risk Assessment
   - **Overall risk**: Low / Medium / High
   - **Blast radius**: X files, Y functions impacted
   - **Test coverage**: N changed functions covered / M total

   ### File-by-File Review
   #### <file_path>
   - Changes: <description>
   - Impact: <who depends on this>
   - Issues: <bugs, style, concerns>

   ### Missing Tests
   - <function_name> in <file> - no test coverage found

   ### Recommendations
   1. <actionable suggestion>
   2. <actionable suggestion>

Tips

  • For large PRs, focus on the highest-impact files first (most dependents)
  • Use `semantic_search_nodes_tool` to find related code the PR might have missed
  • Check if renamed/moved functions have updated all callers
Read more
Ships withcode-review-graph

Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo workflows.

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Python
Language
MIT
License
7d ago
Last commit
5mo ago
Created

Repo: tirth8205/code-review-graph