Skills Artificial Intelligence LLM Prompt Formatting and Context Retrieval

LLM Prompt Formatting and Context Retrieval

v20260707
chat-format
This utility formats prompts for multiple Large Language Model providers (including Anthropic, OpenAI, Gemini, and Ollama) using standardized chat templates. Furthermore, it enables the creation and utilization of an HNSW index for advanced context retrieval, making it ideal for building robust Retrieval-Augmented Generation (RAG) pipelines.
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Overview

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
Info
Name chat-format
Version v20260707
Size 1.31KB
Updated At 2026-07-09
Language