NousResearch/hermes-agent

faiss

Fast vector similarity search at billion scale.

16 installs 240K starsUpdated Sep 3, 2026License: MIT

Install

npx skills add NousResearch/hermes-agent@faiss

Runs in your terminal. Adds the skill globally for Claude Code, Cursor, Codex and others; add -g -y to skip prompts.

What it does

FAISS - Efficient Similarity Search Facebook AI's library for billion-scale vector similarity search. When to use FAISS Use FAISS when: - Need fast similarity search on large vector datasets (millions/billions) - GPU acceleration required - Pure vector similarity (no metadata filtering needed) - High throughput, low latency critical - Offline/batch processing of embeddings Metrics: - 31,700+ GitHub stars - Meta/Facebook AI Research - Handles billions of vectors - C++ with Python bindings Use alternatives instead: - Chroma/Pinecone: Need metadata filtering - Weaviate: Need full database…

Excerpt from the skill's own SKILL.md. Read the full file on GitHub before installing: skills run with your agent's permissions.

View source on GitHub

Before you install

Skills are plain text instructions the agent follows, sometimes with scripts. Check the source, prefer repositories with many installs and stars, and read any script it ships.

Categories

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Search skills

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