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AI/MLruvnet

chat-format

Format prompts for different LLM providers with chat templates and HNSW-powered context retrieval

Stars
56,726
Source
ruvnet/claude-flow
Updated
2026-05-31
Slug
ruvnet--claude-flow--chat-format
View on GitHubRaw SKILL.md

// install — copy + paste into any project

mkdir -p .claude/skills && curl -fsSL https://raw.githubusercontent.com/ruvnet/claude-flow/HEAD/plugins/ruflo-ruvllm/skills/chat-format/SKILL.md -o .claude/skills/chat-format.md

Drops the SKILL.md into .claude/skills/chat-format.md. Works with Claude Code, Cursor, and any agent that loads SKILL.md files from .claude/skills/.

Chat Format

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

When to use

When preparing prompts for different LLM providers (Claude, GPT, Gemini, Ollama) or building RAG pipelines with HNSW-powered context retrieval.

Steps

  1. Format chat — call mcp__claude-flow__ruvllm_chat_format with messages and target provider
  2. Create HNSW index — call mcp__claude-flow__ruvllm_hnsw_create for context retrieval
  3. Add documents — call mcp__claude-flow__ruvllm_hnsw_add to index documents
  4. Route query — call mcp__claude-flow__ruvllm_hnsw_route to find relevant context
  5. Check status — call mcp__claude-flow__ruvllm_status for provider availability

Supported providers

  • Anthropic (Claude) — native format
  • OpenAI (GPT) — chat completion format
  • Google (Gemini) — generative AI format
  • Ollama — local model format
  • Cohere — generate/chat format