Chat Format

This handles the tedious work of reformatting prompts between different LLM providers so you're not stuck writing conversion logic when you want to switch from Claude to GPT or spin up a local Ollama model. It covers Anthropic, OpenAI, Google, Cohere, and local formats. The HNSW indexing tools are interesting because you get vector similarity search for RAG pipelines without standing up a separate database. Realistically, you'll use the chat formatting constantly if you're building anything multi-provider, and the HNSW stuff is solid for prototyping retrieval features before committing to Pinecone or whatever.

skills.sh installs: 743
GitHub stars: 81.4K
last updated: Aug 21, 2026

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Install

$ npx -y skills add ruvnet/ruflo --skill chat-format --agent claude-code

Installs into .claude/skills of the current project.

Files

Chat Format

Format prompts for multi-provider LLM inference with context retrieval.

When to use

When you need a prompt string in a local model's chat template (for llama.cpp, Ollama or another local runtime), or a small embedding-based router over a handful of patterns. It does not call a model and it does not format for hosted APIs: Anthropic, OpenAI and Gemini take structured messages, not a template string.