fidelis

Skill · PyPI · ★ 24 · graded 2026-10-20Source linked

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. Apache-2.0.

No outside reports on file

fidelis is distributed via PyPI (fidelis-memory); review its source code, dependencies, and requested permissions before use.

Based on public adoption and transparency signals as of Oct 19, 2026. Our opinion, not a code audit or security guarantee.

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What it can access

Local filesNo local folder access notedLOW
Command executionNo shell command runner notedLOW
Network reachLocal or standard API callsLOW
CredentialsNo API token requiredLOW
Package sourcePyPI (fidelis-memory)PUBLIC

Inferred from this listing’s public package details and description. Check the project’s source before installing.

Install

uvx fidelis-memory

All setup options ↓

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About Fidelis

Fidelis is an agent skill focused on Developer tools and Data & databases: 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. Apache-2.0.

It is published on PyPI as fidelis-memory and hosted on GitHub at hermes-labs-ai/fidelis (24 GitHub stars). Based on its public metadata, it operates with standard local or API scope without broad shell execution flags noted.

Setup

These use the package this listing points to. Check the project’s own instructions before running anything.

PyPI command

uvx fidelis-memory

PyPI (pip) command

pip install fidelis-memory

Why this grade

DD — High risk signals

Signal-based grade (1/7 points): public source code. This reflects adoption and transparency, not a code review.

Popularity and upkeep

21/100

GitHub stars: 24
Listing last refreshed: 2026-10-29

These are public popularity signals, not a maintenance check. Look at the repository’s commit history and open issues.

Security reports

No reports found for this package in our research (last checked 2026-10-29).

Check a specific version →

Risks to watch for

Dependency & version pinning: Distributed via PyPI (fidelis-memory). Pin an exact release version or commit SHA rather than floating tags so upstream updates are reviewed first.

How to lower the risk

Least-privilege permissions

Give it access only to the specific folders, accounts or projects it needs, never your whole drive or admin account.
Use a separate, limited API key or login just for this tool so you can switch it off without affecting anything else.

Network isolation

Run it on a work computer or sandbox account, not one holding personal or company-sensitive data.
If your IT team can, limit which websites and services it is allowed to contact.

Monitoring

Check its activity history or logs weekly at first, and look at what it changed or sent.
Turn on alerts for new logins or unusual usage on any account it connects to.

Red flags to watch for

It asks for more access than its job requires, or prompts you to paste passwords.
It suddenly updates with new owners, or starts contacting unfamiliar websites.

Questions

How do I install Fidelis?

Run uvx fidelis-memory (or pip install fidelis-memory) in your terminal. Full setup docs and environment variables are in github.com/hermes-labs-ai/fidelis.

Are there security reports about Fidelis?

No reports found for this package in our research (last checked 2026-10-29). Fidelis currently holds Grade D (High risk signals) based on public adoption and transparency signals. Review the permissions and source repository before granting access to local files, shell commands, or API keys.

Is Fidelis actively maintained?

Fidelis has 24 GitHub stars. Our directory data was last refreshed on 2026-10-29. Check recent commit activity, release tags, and open issues at github.com/hermes-labs-ai/fidelis before pinning it in production.

What are alternatives to Fidelis?

You can compare Fidelis side by side with other Memory skills in the Related tools section on this page, or use the Compare tool on AgentArmorHQ.

Maintain or use Fidelis? Show its live grade in your GitHub README, docs site, or run a check from the terminal before you install.

GitHub README Markdown:

markdown

[![AgentArmorHQ Risk Grade for Fidelis](https://agentarmorhq.com/api/badge/hermes-labs-ai-fidelis)](https://agentarmorhq.com/skills/hermes-labs-ai-fidelis)

HTML embed:

html

<a href="https://agentarmorhq.com/skills/hermes-labs-ai-fidelis"><img src="https://agentarmorhq.com/api/badge/hermes-labs-ai-fidelis" alt="AgentArmorHQ Risk Grade for Fidelis" height="20" /></a>

Terminal check:

terminal

curl -fsSL https://agentarmorhq.com/api/cli | node --input-type=module - check "hermes-labs-ai-fidelis"

Share with your security lead

Need sign-off to use fidelis? Copy this note for Slack, a ticket or a pull request.

### AgentArmorHQ Security Review Memo: fidelis
- **Listing URL:** https://agentarmorhq.com/skills/hermes-labs-ai-fidelis
- **Type:** AI agent skill
- **Risk Grade:** Grade D (High risk signals)
- **Outside Security Advisories on File:** 0
- **Public Adoption:** 24 GitHub stars

#### Permission & Blast-Radius Signals
- **Local files:** No local folder access noted
- **Command execution:** No shell command runner noted
- **Network reach:** Local or standard API calls
- **Credentials:** No API token required
- **Package source:** PyPI (fidelis-memory)

#### Recommended Hardened Setup
- **Command:** `uvx fidelis-memory`
- **Controls:** Pin an exact version in `.mcp.json`, scope access to a single workspace folder, and use a least-privilege read-only token where supported.

_Based on public adoption and transparency signals as of Oct 19, 2026. Our opinion, not a code audit or security guarantee._

Key facts

Type: AI agent skill
Publisher: hermes-labs-ai
Source code: github.com/hermes-labs-ai/fidelis
Install command: pip install fidelis-memory
Est. context load: ~80 tokens idle · ~1.4k tokens when active (on-demand skill)
Popularity: 24 GitHub stars
Last updated: 2026-10-29
Last graded: 2026-10-20

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