What is automem CLAUDE.md?

Project instructions for AutoMem, a Flask service that stores long-term memory for AI assistants. They describe the project, its FalkorDB graph database and Qdrant search database, setup, development commands, and tests.

Use them when developing AutoMem, starting its local services, running unit or integration tests, viewing logs, or running benchmarks.

They give a coding agent the project context and the approved commands for working safely in the repository. This reduces guesswork when setting up, running, or testing the service.

How verygoodplugins/automem configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to verygoodplugins/automem. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/verygoodplugins/automem/develop/CLAUDE.md

Clone the repo

git clone --depth 1 https://github.com/verygoodplugins/automem

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/verygoodplugins/automem/claude-md/github.svg)](https://agentmods.dev/instructions/verygoodplugins/automem/claude-md)

Your own site

<a href="https://agentmods.dev/instructions/verygoodplugins/automem/claude-md"><img src="https://agentmods.dev/badge/instructions/verygoodplugins/automem/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/instructions/verygoodplugins/automem/claude-md"><img src="https://agentmods.dev/badge/instructions/verygoodplugins/automem/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 4,543 This file is loaded in full into every session.

When invoked 4,543 The same file — it is already loaded in full.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.04543	$0.04543
Opus 5.5	$0.01817	$0.01817
Sonnet 5.5	$0.00909	$0.00909
Haiku 4.5	$0.00454	$0.00454

Measured 2mo ago against content hash 856b778c74c1, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

automem CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

CLAUDE.md · 379 lines

How it starts

The opening of the file, as written. The whole thing — 379 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Project Overview

AutoMem is a Flask-based memory service that provides durable memory storage for AI assistants using FalkorDB (graph database) for relationships and Qdrant (vector database) for semantic search. The service gracefully degrades when Qdrant is unavailable, ensuring graph operations always succeed.

Development Commands

# Setup environment
make install          # Create .venv, install deps, and keep venv -> .venv
source .venv/bin/activate

# Development
make dev             # Start full stack (FalkorDB + Qdrant + API) via Docker
make stop            # Stop local containers (keep volumes)
make test            # Run pytest test suite (unit tests only)
make test-integration # Run all tests including integration tests (starts Docker)
make test-live       # Run integration tests against live Railway server
make logs            # Follow Flask API logs
make clean           # Clean up Docker containers/volumes

# Benchmarking
make test-locomo      # Run LoCoMo benchmark against local server
make test-locomo-live # Run LoCoMo benchmark against Railway server

# Recall Quality Lab (data-driven scoring tests)
make lab-clone        # Clone production data to local Docker
make lab-queries      # Generate test queries from local data
make lab-test CONFIG=baseline    # Run recall test with a config
make lab-compare CONFIG=fix_v1 BASELINE=baseline  # A/B compare configs
make lab-sweep PARAM=SEARCH_WEIGHT_VECTOR VALUES=0.20,0.30,0.40,0.50

# Code quality
black .              # Format Python code
flake8               # Lint Python code

# Testing specific features
pytest                               # Run all tests
pytest tests/test_app.py -v         # Run with verbose output
pytest -k test_store_memory          # Run specific test by name
pytest tests/test_consolidation_engine.py::TestMemoryConsolidator  # Run test class

# Deployment
make deploy          # Deploy to Railway
make status          # Check deployment status

Read the full file on GitHub · 379 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 379 lines · 4,543 tokens per session scan A 856b778c74c1

Subscribe to this mod's changes

automem CLAUDE.md is an instructions file published in the GitHub repository verygoodplugins/automem (827 stars, last pushed 4d ago), licensed MIT. It adds 4,543 tokens to every session, about $0.0182 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Databases LLM Memory and context Redis and cache ai ai-memory anthropic falkordb graph-database

automem CLAUDE.md next to 6 instructions from other repositories
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automem: Instructions file for Claude Code