What is machine-learning-library AGENTS.md?

A repository guide that tells coding agents how to work with a machine-learning library, including its files, an experimental algorithm, document metadata, and how to retrieve information.

Use it when an agent needs to navigate this library, work with the experimental APRL algorithm, follow the document format, or retrieve information from the project.

It gives agents the project-specific rules and background they need to make consistent changes and find the right learning material.

How ATOM00blue/machine-learning-library configures Codex and OpenCode

Reuse

Borrowing it

Nothing to install: this file belongs to ATOM00blue/machine-learning-library. 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/ATOM00blue/machine-learning-library/main/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/ATOM00blue/machine-learning-library

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/atom00blue/machine-learning-library/agents-md/github.svg)](https://agentmods.dev/instructions/atom00blue/machine-learning-library/agents-md)

Your own site

<a href="https://agentmods.dev/instructions/atom00blue/machine-learning-library/agents-md"><img src="https://agentmods.dev/badge/instructions/atom00blue/machine-learning-library/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/atom00blue/machine-learning-library/agents-md"><img src="https://agentmods.dev/badge/instructions/atom00blue/machine-learning-library/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 1,150 This file is loaded in full into every session.

When invoked 1,150 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	$0.01150	$0.01150
Opus 5.5	$0.00460	$0.00460
Sonnet 5.5	$0.00230	$0.00230
Haiku 4.5	$0.00115	$0.00115

Measured 2mo ago against content hash 860421d53770, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

machine-learning-library 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 · 93 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

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 · 93 lines · 1,150 tokens per session scan A 860421d53770

Subscribe to this mod's changes

machine-learning-library AGENTS.md is an instructions file published in the GitHub repository ATOM00blue/machine-learning-library (261 stars, last pushed 2mo ago), with no licence file. It adds 1,150 tokens to every session, about $0.0046 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.

Data and AI LLM RAG and vectors arxiv corpus dataset deep-learning

machine-learning-library AGENTS.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
machine-learning-library AGENTS.mdATOM00blue/machine-learning-library	Instructions file	261	2mo ago	none	A	1,150	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	today	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

machine-learning-library: Instructions file for Codex