rlm-skill
CommunityProcess massive docs beyond context with RLM.
Software Engineering#document processing#chunking#rlm#multi-format ingestion#hierarchical aggregation#cross-file analysis#directory processing
Authordanielsimonjr
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill enables processing content that exceeds traditional language model context windows by loading data into a Python runtime, chunking intelligently, and synthesizing results across chunks.
Core Features & Use Cases
- Auto-chunking detects document structure (markdown headers, code blocks, JSON) and selects an optimal chunking strategy.
- Pre-filtering with keyword/regex reduces unnecessary LLM calls before processing chunks.
- Hierarchical aggregation recursively combines results to enable analysis of very large contexts, including directories and codebases.
- Multi-format ingestion supports PDF, DOCX, HTML, JSON/JSONL, CSV, YAML, XML, archives, and 30+ code/text extensions.
- Directory processing enables cross-file analysis and coherent summaries across many files.
Quick Start
Run the RLM processor on a large file, for example: python rlm_processor.py path/to/large_document.txt "What are the key findings?"
Dependency Matrix
Required Modules
pdfplumberpython-docxbeautifulsoup4PyPDF2
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: rlm-skill Download link: https://github.com/danielsimonjr/claude-skills/archive/main.zip#rlm-skill Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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