debug-issue
FeaturedSystematically debug issues using graph-powered code navigation
Code & Development 31,800 stars
2907 forks Updated 1 weeks ago MIT
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Skill Content
## Debug Issue
Trace a bug through the knowledge graph before reading source.
### Steps
1. Call `semantic_search_nodes_tool` to find code related to the issue.
2. Call `query_graph_tool` with `callers_of` and `callees_of` to trace the call chain in both directions.
3. Call `get_flow_tool` for the execution path that reaches the suspect code. Its entry point is where the bug is triggered.
4. Call `detect_changes_tool` to check whether a recent change caused the issue.
5. Call `get_impact_radius_tool` on the suspect files to see what a fix would affect.
## 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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