review-changes

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Perform a structured code review using change detection and impact

Code & Development 31,800 stars 2907 forks Updated 1 weeks ago MIT

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Skill Content

## Review Changes Review a change set with risk scores and blast radius from the knowledge graph. ### Steps 1. Call `detect_changes_tool` for risk-scored changed functions, test gaps and affected flows. 2. Call `get_affected_flows_tool` only when you need the steps of an affected flow. 3. For each high-risk function, call `query_graph_tool` with `pattern="tests_for"` to check test coverage. 4. Call `get_impact_radius_tool` when the blast radius is not clear from step 1. 5. Suggest specific test cases for untested changes. ### Output Format Group findings by risk level (high, medium, low). For each finding give what changed and why it matters, its test coverage, and the suggested fix. End with a merge recommendation. ## Token Efficiency Rules - Call `get_minimal_context_tool(task="<your task>")` before any other graph tool. - Pass `detail_level="minimal"` wherever a tool accepts it. Use "standard" only when minimal is not enough. - Prefer a targeted `query_graph_tool` call over a broad listing call. - Budget: about five tool calls and 800 tokens of graph output per task. - Read the implementation and its tests before changing code. The graph narrows scope; it does not replace the source.

Details

Author
tirth8205
Repository
tirth8205/code-review-graph
Created
7 months ago
Last Updated
1 weeks ago
Language
Python
License
MIT

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