Skills Artificial Intelligence Format LLM Prompts with Context Retrieval

Format LLM Prompts with Context Retrieval

v20260716
chat-format
This tool formats prompts for various Large Language Model (LLM) providers, including Anthropic, OpenAI, Gemini, and Ollama. It is essential for building robust Retrieval-Augmented Generation (RAG) pipelines. Users can format messages, create HNSW indexes from documents, route relevant context, and manage provider status, ensuring compatibility across different AI ecosystems.
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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__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
Info
Name chat-format
Version v20260716
Size 1.43KB
Updated At 2026-07-18
Language