analyzing-codebases
Generates LLM-optimized code context with function call graphs, side effect detection, and incremental updates. Processes JavaScript/TypeScript codebases to create compact semantic representations including multi-level summaries, entry point identification, and hash-based change tracking. Provides 74-97% token reduction compared to reading raw source files. Useful for understanding code architecture, debugging complex systems, reviewing pull requests, and onboarding to unfamiliar projects.
Installation
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
View source ↗GuidesSkill instructions
Features and purpose
Generates LLM-optimized code context with function call graphs, side effect detection, and incremental updates. Processes JavaScript/TypeScript codebases to create compact semantic representations including multi-level summaries, entry point identification, and hash-based change tracking. Provides 74-97% token reduction compared to reading raw source files. Useful for understanding code architecture, debugging complex systems, reviewing pull requests, and onboarding to unfamiliar projects.
Quick start
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
Guides ↗Examples
Read the usage examples in the source repository.
View source ↗Source history
- Indexed on
- 2026-01-20
- Index updated
- 2026-01-26
- Branch
- main
Index and sync dates describe this directory. View the source repository for code history.
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