Process large codebases with parallel agents using map-reduce.
npx skills add https://github.com/guia-matthieu/clawfu-skills --skill rlm-guia-matthieu
Please help me install this Agent Skill. Skill: rlm Source: https://github.com/guia-matthieu/clawfu-skills/tree/main/skills/meta/rlm Command: npx skills add https://github.com/guia-matthieu/clawfu-skills --skill rlm-guia-matthieu
This Skill tackles the challenge of analyzing and processing massive codebases that exceed typical context window limitations, preventing context rot and enabling deep analysis.
Use the rlm skill to find all usages of the 'getUser' function across the entire project.
High-intent search queries and answers about installing and using this skill.
To analyze a large codebase exceeding context limits, you can use the Recursive Language Model pattern to treat code as an external environment. This orchestrates parallel background agents using a map-reduce pattern to process files in manageable chunks, preventing context degradation.
The best way to find function usages across a massive project is applying a map-reduce pattern with parallel agents. This approach slices the large codebase programmatically, ensuring agents work with fresh context to accurately locate every instance of the target function.
Yes, you can use bash tools like find and grep for context management on massive codebases. A native mode supports these standard command-line utilities, while a strict mode utilizes Python scripts for dense data analysis and programmatic slicing of large files.
Treating context as an external resource prevents context rot by ensuring parallel agents process code in isolated, manageable chunks. This map-reduce orchestration feeds agents fresh information, avoiding the degradation that occurs when exceeding typical context window limitations.
No, Python scripts are not strictly required for file slicing. You can operate in native mode using standard bash utilities like find and grep, or switch to strict mode with Python scripts when you need dense data analysis and programmatic slicing of large files.
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