Is it suitable for production data?

Yes, it supports production-grade API providers like OpenAI and DeepSeek via LiteLLM for higher reliability and cost-effective large-scale data processing.

What is an RLM Orchestrator?

Recursive Language Models (RLM) allow for processing data sets far larger than an LLM's context window by iteratively analyzing chunks through a structured JSON protocol and specialized toolsets.

Can I use this with local models?

Yes, it fully supports Ollama. However, 32B+ parameter models are recommended for the 'root' role to ensure the JSON protocol is followed reliably.

Why does this skill require Rust and WASM?

RLM uses Rust for high-performance orchestration and WASM for secure, portable code execution that can be generated by LLMs to process data locally without environment-specific conflicts.

How does it handle Windows-specific build issues?

The skill includes automated logic to install MSVC Build Tools and correctly configure the Rust toolchain via winget, preventing common 'link.exe' and path errors.

RLM Project Assistant

Name: RLM Project Assistant
Author: evolv3ai

byevolv3ai

0•

数据科学与机器学习

Orchestrates Recursive Language Models (RLM) to process and analyze massive datasets and files exceeding 10MB using Rust and WASM.

The RLM Project Assistant enables Claude to manage the Recursive Language Models (RLM) Orchestrator, a framework designed to bypass standard context window limitations. By leveraging Rust-based builds and WebAssembly (WASM) compilation targets, this skill allows users to analyze contexts 100x larger than typical LLM limits. It automates the configuration of local (Ollama) and cloud (DeepSeek, OpenAI) providers, handles complex MSVC build tool requirements on Windows, and implements an iterative JSON protocol for reliable large-scale data analysis and log processing.

主要功能

010 GitHub stars

02WASM-powered parallel data analysis and mapreduce workflows

03Multi-provider LLM orchestration supporting Ollama, LiteLLM, DeepSeek, and OpenAI

04Automated Rust and WASM toolchain configuration and environment detection

05Smart bypass logic to optimize performance for small context tasks

06Recursive processing of arbitrarily large files (10MB+) via JSON command protocol

使用场景

01Analyzing massive log files or documentation sets that exceed standard token limits

02Troubleshooting Rust-to-WASM compilation errors and environment setup

03Setting up private, local LLM-based data processing pipelines with Ollama

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add evolv3ai/claude-skills-archive rlm-project-assistant

For use in Claude.ai and ChatGPT

Download Skill