ag2-assistant AGENTS.md

ag2-assistant AGENTS.md is an instructions file for Codex, OpenCode from ag2ai/ag2-assistant. It costs 3,252 tokens per session, scanned A, original, Apache-2.0.

A contributor guide for AG2 Assistant, an open-source personal AI assistant built on the AG2 framework. It covers setup, AI-assisted contributions, coding style, and checks before publishing changes.

In plain words
What is it for?
Setting up development, installing optional integrations, running formatting and safety checks, and preparing responsible pull requests.
Why use it?
It clarifies the project's expectations and helps contributors run the same checks used by its automated build system before sharing code.

Instructions file for CodexOpenCode

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/ag2ai/ag2-assistant/agents-md
Clone the repo
git clone --depth 1 https://github.com/ag2ai/ag2-assistant

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.

agentmods badge for ag2-assistant AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/ag2ai/ag2-assistant/agents-md.svg)](https://agentmods.dev/instructions/ag2ai/ag2-assistant/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/ag2ai/ag2-assistant/agents-md"><img src="https://agentmods.dev/badge/instructions/ag2ai/ag2-assistant/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 3,252 This file is loaded in full into every session.
When invoked 3,252 The same file — it is already loaded in full.
Security scan A 0 findings. 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 $0.03252 $0.03252
Opus 5 $0.01626 $0.01626
Sonnet 5 $0.00650 $0.00650
Haiku 4.5 $0.00325 $0.00325

Measured 3d ago against content hash fbe1580932e0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ag2-assistant 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 3d 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 · 237 lines

How it starts

The opening of the file, as written. The whole thing — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AG2 Assistant — Development Guidelines

AG2 Assistant (package ag2-assistant) is an open-source personal AI assistant built on AG2's framework. This file is the contributor guide for humans and AI coding agents alike. For a product overview see README.md; for the system design see docs/architecture.md.

AI-assisted contribution policy

We welcome AI-assisted contributions — but you remain responsible for everything you submit: code, tests, issues, and PR descriptions. Before opening a PR, read .github/AI_POLICY.md. In short: understand and test what you submit, make the PR description reflect the real diff, and be ready to explain the change in your own words. Fill in .github/PULL_REQUEST_TEMPLATE.md and only tick a checklist box once it is actually true.

Development setup

python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"     # add ",google" for the Gmail/Calendar/Drive extra
pre-commit install          # run the lint/format/safety hooks on every commit

Checks (run these before you push)

These are the same checks CI runs. They are advisory: the repository has no rulesets, so a red pull request is reported by the CI status check rather than blocked by it. (Classic branch protection needs admin to read, so it has not been ruled out. To enforce this, require the single CI status check — it stays one name as the test matrix grows.)

ruff check .                       # lint
ruff format .                      # auto-format (use --check to verify only)
mypy                               # typecheck src/assistant (target is configured; pass no path)
pytest -m "not integration" -q     # unit tests — no API key needed
npm --prefix web run check         # typecheck the SPA (svelte-check, strict)
npm --prefix web test              # SPA unit tests (node:test over web/src/**/*.test.ts)
npm --prefix web run build         # rebuild the SPA bundle if you touched web/

Read the full file on GitHub · 237 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. 3d ago First seen · 237 lines · 3,252 tokens per session scan A fbe1580932e0

Subscribe to this mod's changes

ag2-assistant AGENTS.md is an instructions file published in the GitHub repository ag2ai/ag2-assistant (11 stars, last pushed 10d ago), licensed Apache-2.0. It adds 3,252 tokens to every session, about $0.0163 per session on Opus 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.

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