LLM Prompt Formatting with RAG Context

Formats prompts for different LLM providers (Claude, GPT, Gemini, etc.) and uses HNSW search for context retrieval.

Sby Skills Guide Bot
Data & AIIntermediate
108/29/2026
Claude Code
#prompt-formatting#llm#rag#hnsw#context-retrieval

Recommended for


name: chat-format description: Format prompts for different LLM providers with chat templates and HNSW-powered context retrieval argument-hint: "<prompt> [--provider anthropic|openai|gemini|ollama|cohere]" allowed-tools: mcp__plugin_ruflo-core_ruflo__ruvllm_chat_format mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_create mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_add mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_route mcp__plugin_ruflo-core_ruflo__ruvllm_status Bash

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__plugin_ruflo-core_ruflo__ruvllm_chat_format with messages and target provider
  2. Create HNSW index — call mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_create for context retrieval
  3. Add documents — call mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_add to index documents
  4. Route query — call mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_route to find relevant context
  5. Check status — call mcp__plugin_ruflo-core_ruflo__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
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