Generate Mermaid and JSON call graphs from Python AST analysis.
npx skills add https://github.com/oiiiwjh/skills --skill python-call-graph
Please help me install this Agent Skill. Skill: python-call-graph Source: https://github.com/oiiiwjh/skills/tree/main/python-call-graph Command: npx skills add https://github.com/oiiiwjh/skills --skill python-call-graph
This Skill helps developers understand the complex relationships and dependencies within Python codebases by generating static call graphs, eliminating the need for manual code tracing or runtime execution.
Use the python-call-graph skill to generate a Mermaid and JSON call graph for the local repository located at '/path/to/your/python/project'.
High-intent search queries and answers about installing and using this skill.
Generate a static call graph for a Python repository by analyzing the codebase using Abstract Syntax Trees (AST) without executing it, producing Mermaid diagrams and JSON data to visualize function dependencies.
AST-based dependency analysis works by parsing Python code structures into an Abstract Syntax Tree to statically identify function and method calls, mapping out code relationships without runtime execution.
Yes, you can limit the depth of a Python call graph and focus the analysis on specific entrypoints, allowing you to visualize a targeted subset of function dependencies rather than the entire codebase.
No, static call graph analysis does not fully support dynamic dispatch and runtime behaviors in Python, as it relies solely on AST parsing rather than executing the code to resolve runtime method calls.
The best way to visualize Python code structure during onboarding is generating a Mermaid diagram of the main application entrypoint, which quickly clarifies project architecture and data flow dependencies.
Yes, you can get JSON output from a Python call graph for downstream processing, providing structured data of function and method calls alongside visual Mermaid diagrams for code visualization.
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