agentmods.dev

automem AGENTS.md

Repository instructions for Automem, a Python memory service with a Flask API, data stores, tests, benchmarks, documentation, and optional connections to other services. A virtual environment keeps its Python dependencies separate from the rest of the system.

In plain words
What is it for?
Use them when changing the Automem API or storage code, running unit or integration tests, starting its Docker-based local stack, or working with benchmarks and maintenance scripts.
Why use it?
They show how the repository is organized and which commands start services, run tests, and manage development, reducing setup mistakes and confusion about benchmark tools.

Instructions file for CodexOpenCode

805 +2 4d ago A scan 1,708 tokens original MIT
View the source file verygoodplugins/automem
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/verygoodplugins/automem/agents-md
Clone the repo
git clone --depth 1 https://github.com/verygoodplugins/automem

Made for: Codex, OpenCode.

Per session 1,708 This file is loaded in full into every session.
When invoked 1,708 The same file — it is already loaded in full.
Security scan A 1 finding. Scan, not verified.
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.

ModelPer sessionOnce invoked
Fable 5 $0.01708 $0.01708
Opus 5 $0.00854 $0.00854
Sonnet 5 $0.00342 $0.00342
Haiku 4.5 $0.00171 $0.00171

Measured 2d ago against content hash a7b578d0ec2c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

automem AGENTS.md scanned grade A with 1 finding 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 2d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- `make deploy` / `make status`: Deploy/check Railway. Quick health: `curl :8001/health`.
AGENTS.md · 99 lines

How it starts

The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Repository Guidelines

Project Structure & Modules

  • automem/: Core package. Notable dirs: api/ (Flask blueprints), utils/, stores/, config.py.
  • app.py: Flask API entry point used in local/dev and tests.
  • tests/: Pytest suite (test_*.py), plus legacy benchmark harnesses under tests/benchmarks/.
  • benchmarks/: Snapshot-based benchmark system. See EXPERIMENT_LOG.md for current baselines and results.
  • scripts/bench/: Benchmark tooling (ingest, eval, compare, health check).
  • docs/: API, testing, deployment, monitoring, and env var references.
  • scripts/: Maintenance and ops helpers (backup, reembed, health monitor). See the canonical scripts catalog for lifecycle and usage.
  • mcp-sse-server/: Optional MCP bridge used in some deployments.

Build, Test, and Development

  • make install: Create .venv (and symlink venv -> .venv) and install dev deps. Prefers Python 3.12 and fails fast on incompatible python3.
  • source .venv/bin/activate: Activate the virtualenv.
  • make dev: Start local stack via Docker (FalkorDB, Qdrant, API).
  • make test: Run unit tests (fast, no services).
  • make test-integration: Start Docker and run full integration tests.
  • make fmt / make lint: Format with Black/Isort and lint with Flake8.
  • make bench-eval BENCH=locomo-mini: Run snapshot-based benchmark (~2 min). See Benchmarking section below.
  • make deploy / make status: Deploy/check Railway. Quick health: curl :8001/health.

Coding Style & Naming

  • Python with type hints. Indent 4 spaces; line length 100 (Black).
  • Tools: Black, Isort (profile=black), Flake8; pre-commit hooks available.
  • Run pre-commit install and make fmt && make lint before committing.
  • Naming: modules/functions snake_case, classes PascalCase, constants UPPER_SNAKE_CASE.

Testing Guidelines

  • Framework: Pytest. Place tests in tests/ named test_*.py.
  • Unit tests: make test.
  • Integration: make test-integration (requires Docker). See docs/TESTING.md for env flags and live testing options.
  • Add/adjust tests for new endpoints, stores, or utils; prefer fixtures over globals.

Read the full file on GitHub · 99 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.

  1. 2d ago First seen · 99 lines · 1,708 tokens per session scan A a7b578d0ec2c

Subscribe to this mod's changes

automem AGENTS.md is an instructions file published in the GitHub repository verygoodplugins/automem (805 stars, last pushed 4d ago), licensed MIT. It adds 1,708 tokens to every session, about $0.0085 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

LLMaiai-memoryanthropicfalkordbgraph-database
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