Why use RLM instead of standard file reading?

Standard tools often crash or hit context limits with files over 10MB. RLM uses iterative commands to analyze file structures and extract data without loading the entire file into the LLM's active context.

Which LLM providers are recommended for this skill?

For reliable JSON protocol handling with large files, OpenAI GPT-4o, OpenRouter, or DeepSeek API are highly recommended. Local models smaller than 70B parameters may be unreliable for the RLM protocol.

Does it support ChatGPT exports?

Yes, the skill includes specific logic and query patterns for both Claude (Anthropic) and ChatGPT (OpenAI) JSON export structures.

Can this process files larger than 70MB?

Yes, by using the recommended hybrid Python/RLM approach. Python handles the initial metadata extraction instantly, while RLM performs the deep content analysis on specific segments.

Obsidian Large File Processor (RLM)

Name: Obsidian Large File Processor (RLM)
Author: evolv3ai

byevolv3ai

0•

生产力与工作流

Processes massive LLM conversation exports and large datasets for Obsidian using Recursive Language Models.

This skill enables Claude to handle exceptionally large files (10MB to 70MB+) that typically exceed standard context limits by utilizing Recursive Language Models (RLM). It is specifically optimized for importing massive Claude and ChatGPT conversation archives into Obsidian vaults, providing automated triage, metadata extraction, and structured markdown generation. By offloading heavy processing to an RLM server, it ensures reliable analysis of large exports without crashing or losing context, making it an essential tool for personal knowledge management power users who need to organize thousands of AI interactions.

主要功能

01Automated triage and categorization of conversation threads

02Hybrid workflow support combining Python speed with RLM analysis

03Structured metadata extraction including dates and message counts

040 GitHub stars

05Recursive processing of 10MB+ JSON and text exports

06Generation of Obsidian-ready frontmatter, wikilinks, and tags

使用场景

01Performing bulk triage on conversation archives to filter by topic, length, or code content

02Analyzing massive JSON datasets to identify high-value insights without context overflow

03Migrating thousands of Claude or ChatGPT chat histories into an Obsidian vault

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add evolv3ai/claude-skills-archive obsidian-rlm

For use in Claude.ai and ChatGPT

Download Skill