hermes-labs-ai

Fidelis — AI skill for Claude Code

AI community

Zero-LLM agent memory for Claude Code and AI agents: local-first BM25, dense-vector, and reciprocal-rank-fusion retrieval.

How to install Fidelis

This entry records only its repository, not the path inside it, so there is no exact command to give. Open hermes-labs-ai/fidelis and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Fidelis does

Zero-LLM agent memory for Claude Code and AI agents: local-first BM25, dense-vector, and reciprocal-rank-fusion retrieval. Returns original passages verbatim by default. Available on PyPI as fidelis-memory. MIT.

Alternatives in AI

SEO Geo Claude Skills — 20 SEO & GEO skills for Claude Code, Cursor, Codex, and 35+ AI agents 888 ★
Codeseek — Rust-powered code intelligence CLI for AI coding agents 764 ★
K Dense Byok — An AI co-scientist powered by Claude Scientific Skills running on your desktop 583 ★

README

Fidelis Memory

Local-first, zero-LLM memory for Codex, Claude Code, and AI agents.

**73.0% end-to-end QA on LongMemEval-S. 83.2% R@1 retrieval. $0/query. No LLM in the default retrieval path.**

Stop re-explaining context to your agent. fidelis returns your original notes verbatim, local-first, fast, about 60 seconds to install. Your agent already calls an LLM to think; it should not need another one just to remember. Designed for developers. The default zero-LLM retrieval path does not send memory content to an LLM. The documented `fidelis init` service configuration also disables mem0 and Chroma telemetry. That can reduce third-party data exposure, but deployments still own their security and compliance assessment.

[![License: MIT](https://img.shields.io/badge/license-MIT-green)](LICENSE) [![Status: pre-release](https://img.shields.io/badge/status-pre--release-orange)](#known-limitations) [![CI tests: 368 passing](https://img.shields.io/badge/CI%20tests-368%20passing-brightgreen)](tests/) [![Official MCP Registry](https://img.shields.io/badge/MCP%20Registry-active-5b5bd6)](https://registry.modelcontextprotocol.io/v0.1/servers/io.github.hermes-labs-ai%2Ffidelis-memory/versions/0.0.95) [![Made by Hermes Labs](https://img.shields.io/badge/made%20by-Hermes%20Labs-purple)](https://hermes-labs.ai)

your notes / sessions
       ↓
local memory store      (~/.cogito/, fully local)
       ↓
fidelis retrieval       (BM25 + dense + RRF, no LLM)
       ↓
original passages       (verbatim, never rephrased)
       ↓
Codex / Claude Code / your agent

What fidelis is:

fast - ~216 ms local retrieval (full benchmark mean; vector-only path is faster)
cheap - $0/query retrieval cost
private - local memory store by default
faithful - original stored passages returned, not paraphrases
proven - benchmarked on LongMemEval-S (470 questions, public benchmark), with raw evidence in [`ex