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richardwhiteiirichardwhiteiiCommunity·1 Agent Skills Included

rlm

Analyze massive files and codebases beyond context limits

Processes files and datasets too large for a standard context window by loading them externally, chunking them, and running parallel sub-queries. Eliminates context-overflow errors when analyzing huge log files, multi-file codebases, or long research documents. Supports regex filtering, sandboxed Python execution, and free local inference via Ollama to keep costs low.
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npx skills add richardwhiteii/rlm --all -g -y

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richardwhiteiirichardwhiteii

RLM (Recursive Language Model) Skill

Load large text outside the prompt, chunk it, and run batched sub-queries with aggregation.

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Frequently Asked Questions

FAQPage Schema
How to install RLM?▼

Run `npx skills add richardwhiteii/rlm --all -g -y` in your terminal to install the skill globally.

How to analyze files too large for the context window?▼

RLM loads the content as an external variable, splits it into chunks, and runs parallel sub-queries so you can analyze files of 10M+ tokens without overflow errors.

Can RLM summarize large log files?▼

Yes. It filters error lines with regex, chunks the results, and aggregates findings into a clear summary of error patterns and counts.

Does RLM work with Claude Code?▼

Yes. It runs as an MCP server for Claude Code and can auto-detect large files, so your agent uses it automatically when needed.

Can I run RLM sub-queries for free?▼

Yes. Set the provider to Ollama with a local model to run all sub-queries on your own hardware at zero cost.

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