What is learn-opencode AGENTS.md?

Repository instructions for learn-opencode, a project about developing software agents. They describe the project, setup commands, source-submodule initialization, and what to do after the first clone.

Use them when working in the learn-opencode repository, especially during setup, cloning, or source-submodule work.

They give the coding agent project-specific rules and setup context, reducing the chance of using the wrong commands or skipping required initialization.

How ZeroZ-lab/learn-opencode configures Codex and OpenCode

Reuse

Borrowing it

Nothing to install: this file belongs to ZeroZ-lab/learn-opencode. 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/ZeroZ-lab/learn-opencode/master/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/ZeroZ-lab/learn-opencode

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/zeroz-lab/learn-opencode/agents-md/github.svg)](https://agentmods.dev/instructions/zeroz-lab/learn-opencode/agents-md)

Your own site

<a href="https://agentmods.dev/instructions/zeroz-lab/learn-opencode/agents-md"><img src="https://agentmods.dev/badge/instructions/zeroz-lab/learn-opencode/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/zeroz-lab/learn-opencode/agents-md"><img src="https://agentmods.dev/badge/instructions/zeroz-lab/learn-opencode/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 1,766 This file is loaded in full into every session.

When invoked 1,766 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 unknown 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	$0.01766	$0.01766
Opus 5.5	$0.00706	$0.00706
Sonnet 5.5	$0.00353	$0.00353
Haiku 4.5	$0.00177	$0.00177

Measured 2mo ago against content hash f2ab12aea380, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

learn-opencode 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 · 241 lines

The source is not reproduced here

No licence file

Read it on GitHub

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 · 241 lines · 1,766 tokens per session scan A f2ab12aea380

Subscribe to this mod's changes

learn-opencode AGENTS.md is an instructions file published in the GitHub repository ZeroZ-lab/learn-opencode (124 stars, last pushed 10mo ago), with no licence file. It adds 1,766 tokens to every session, about $0.0071 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.

learn-opencode AGENTS.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
learn-opencode AGENTS.mdZeroZ-lab/learn-opencode	Instructions file	124	10mo ago	none	A	1,766	Codex, OpenCode
vscode buildNext.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	9,719	GitHub Copilot
next.js AGENTS.mdvercel/next.js	Instructions file	143k	yesterday	MIT	A	7,461	Codex, OpenCode
langchain AGENTS.mdlangchain-ai/langchain	Instructions file	149k	yesterday	MIT	A	4,680	Codex, OpenCode
vscode oss-third-party-notices.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	5,516	GitHub Copilot
vscode copilot-instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	3,093	GitHub Copilot
deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness	Instructions file	274k	2d ago	MIT	A	4,313	Codex, OpenCode

learn-opencode: Instructions file for Codex