What is Acontext AGENTS.md?

A navigation and development guide for Acontext, a system that gives production AI agents reusable skills and memory. It maps the repository's Python and TypeScript software development kits, command-line tool, server, dashboard, packages, tests, and documentation.

Use it when modifying Acontext's clients, command-line tool, server, dashboard, sandbox package, tests, landing page, or documentation.

It shows where each part of the system lives and requires a written plan before implementation. This makes changes easier to locate and keeps development work organized.

How memodb-io/Acontext configures Codex and OpenCode

About the project

Acontext is an open-source memory layer for AI agents that records useful knowledge from agent runs as editable skill files. Agent builders use it to preserve, inspect, share, and reuse what agents learn across frameworks, and the catalogue includes hooks, skills, instructions, rules, an MCP, and a plugin for working with it.

memodb-io/Acontext · 3,698 stars · on GitHub · acontext.io

Reuse

Borrowing it

Nothing to install: this file belongs to memodb-io/Acontext. 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/memodb-io/Acontext/main/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/memodb-io/Acontext

Made for: Codex, OpenCode.

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/memodb-io/acontext/agents-md/github.svg)](https://agentmods.dev/instructions/memodb-io/acontext/agents-md)

Your own site

<a href="https://agentmods.dev/instructions/memodb-io/acontext/agents-md"><img src="https://agentmods.dev/badge/instructions/memodb-io/acontext/agents-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/memodb-io/acontext/agents-md"><img src="https://agentmods.dev/badge/instructions/memodb-io/acontext/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 2,445 This file is loaded in full into every session.

When invoked 2,445 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	$0.02445	$0.02445
Opus 5.5	$0.00978	$0.00978
Sonnet 5.5	$0.00489	$0.00489
Haiku 4.5	$0.00245	$0.00245

Measured 2mo ago against content hash 77be58c9dacb, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

Acontext AGENTS.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.

AGENTS.md · 102 lines

How it starts

The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Acontext

Acontext is Agent Skills as a Memory Layer for production AI Agents

Python SDK: src/client/acontext-py/
TypeScript SDK: src/client/acontext-ts/
CLI Tool: src/client/acontext-cli/
API: src/server/api/
CORE: src/server/core/
Dashboard: dashboard/
Dashboard (OSS): src/server/ui/
OpenClaw Plugin: src/packages/openclaw/ (npm: @acontext/openclaw)
Sandbox Cloudflare: src/packages/sandbox-cloudflare/ — a scaffolding/template package (npm: @acontext/create-sandbox-cloudflare). Its prepublishOnly script copies src/server/sandbox/cloudflare/ into template/ with variable substitution, so changes to the Cloudflare Worker source in src/server/sandbox/cloudflare/ are automatically picked up on publish.
E2E Tests: src/server/tests/e2e/ — integration tests that run the full stack (API + Core + deps) via docker-compose.test.yml. When modifying server-side behavior, check if e2e coverage should be added or updated.
Landing Page: landingpage
Documentation: docs/

Plan-driven Development

You must make a markdown plan at plans/ before you implement any my request, otherwise I will reject your implementation.
The plans/ directory is gitignored — plans are kept locally and do not need to be committed or included in PRs.
Remember to update the dev plan after you finish coding.
When every task is completed, make sure you check the task checkbox in the corresponding plan.
A plan should at least contain features/show case, designs overview, TODOS, new deps, test cases sections.
- always use the features/show case to present what you're going to build.
- use checklist in TODOS section, for each checkbox, you must have a clear descripion of what to do and list all the files that will be modified.
- in new deps section, you must list all the new external dependencies that will be added.
- in test cases section, use checklist format to list all the test cases that should be covered.

Read the full file on GitHub · 102 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 · 102 lines · 2,445 tokens per session scan A 77be58c9dacb

Subscribe to this mod's changes

Acontext AGENTS.md is an instructions file published in the GitHub repository memodb-io/Acontext (3,698 stars, last pushed 13d ago), licensed Apache-2.0. It adds 2,445 tokens to every session, about $0.0098 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.

Building agents Memory and context agent agent-development-kit ai-agent context-engineering data-platform self-learning

Acontext AGENTS.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
Acontext AGENTS.mdmemodb-io/Acontext	Instructions file	3.7k	13d ago	Apache-2.0	A	2,445	Codex, OpenCode
vscode buildNext.instructions.mdmicrosoft/vscode	Instructions file	195k	today	MIT	A	9,719	GitHub Copilot
next.js AGENTS.mdvercel/next.js	Instructions file	143k	today	MIT	A	7,461	Codex, OpenCode
langchain AGENTS.mdlangchain-ai/langchain	Instructions file	149k	today	MIT	A	4,680	Codex, OpenCode
vscode oss-third-party-notices.instructions.mdmicrosoft/vscode	Instructions file	195k	today	MIT	A	5,516	GitHub Copilot
vscode copilot-instructions.mdmicrosoft/vscode	Instructions file	195k	today	MIT	A	3,093	GitHub Copilot
deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness	Instructions file	274k	2d ago	MIT	A	4,313	Codex, OpenCode

Acontext: Instructions file for Codex