Does this skill run actual performance benchmarks?

No, it is a pre-profiling tool used to identify 'hot' files and paths to help you determine where you should run your actual profiling and benchmarking tools.

What languages does the Performance Code Path Mapper support?

This skill currently supports Rust, Java, JS/TS (JavaScript/TypeScript), Go, and Python for identifying execution paths.

How does it identify relevant files?

It utilizes repository maps or grep to find entry points, handlers, and call chains associated with specific performance scenarios provided by the user.

What is the limit of files it will analyze?

The skill is constrained to identify and list the most relevant 10-15 files to keep the analysis focused and actionable.

Performance Code Path Mapper

Name: Performance Code Path Mapper
Author: ComposioHQ

byComposioHQ

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1,152

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분석 및 모니터링

Maps execution paths and identifies likely hotspots to streamline performance profiling and optimization workflows.

The Performance Code Path Mapper is a specialized Claude Code skill designed to accelerate performance debugging by identifying critical code paths, entry points, and likely 'hot' files before a profile is even run. By analyzing repository maps, handlers, and complex call chains, it provides a structured overview of the most relevant files involved in a specific scenario. This allows developers to focus their optimization efforts on the high-impact areas of the codebase across major languages like Rust, Java, Python, Go, and TypeScript, ensuring that performance audits are targeted and efficient.

주요 기능

01Automated entry point and handler detection via repository mapping and grep

02Multi-language support for Rust, Java, JS/TS, Go, and Python

03Detailed analysis of call chains, imports, and exports for specific scenarios

04Standardized output format listing evidence for each identified path

05Identification of top candidate files and symbols for performance profiling

061,152 GitHub stars

사용 사례

01Pre-profiling analysis to narrow down the scope of performance bottlenecks

02Understanding critical code paths during onboarding to a new, complex codebase

03Mapping execution flows for high-latency API endpoints or background jobs

주요 기능

01Automated entry point and handler detection via repository mapping and grep

02Multi-language support for Rust, Java, JS/TS, Go, and Python

03Detailed analysis of call chains, imports, and exports for specific scenarios

04Standardized output format listing evidence for each identified path

05Identification of top candidate files and symbols for performance profiling

061,152 GitHub stars

사용 사례

01Pre-profiling analysis to narrow down the scope of performance bottlenecks

02Understanding critical code paths during onboarding to a new, complex codebase

03Mapping execution flows for high-latency API endpoints or background jobs