What is Study-Reinforcement-Learning AGENTS.md?

Repository-specific instructions for a reinforcement-learning study project. They explain the project’s files, review status, and preferred writing style.

Use them when reviewing or editing the Study-Reinforcement-Learning repository, especially when you need to follow its layout or writing conventions.

They give a coding agent the project context it needs, so its changes fit the repository instead of relying on guesswork.

How 0bserver07/Study-Reinforcement-Learning configures Codex and OpenC

Reuse

Borrowing it

Nothing to install: this file belongs to 0bserver07/Study-Reinforcement-Learning. 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/0bserver07/Study-Reinforcement-Learning/master/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/0bserver07/Study-Reinforcement-Learning

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/0bserver07/study-reinforcement-learning/agents-md/github.svg)](https://agentmods.dev/instructions/0bserver07/study-reinforcement-learning/agents-md)

Your own site

<a href="https://agentmods.dev/instructions/0bserver07/study-reinforcement-learning/agents-md"><img src="https://agentmods.dev/badge/instructions/0bserver07/study-reinforcement-learning/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/0bserver07/study-reinforcement-learning/agents-md"><img src="https://agentmods.dev/badge/instructions/0bserver07/study-reinforcement-learning/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 1,901 This file is loaded in full into every session.

When invoked 1,901 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	$0.01901	$0.01901
Opus 5.5	$0.00760	$0.00760
Sonnet 5.5	$0.00380	$0.00380
Haiku 4.5	$0.00190	$0.00190

Measured 7d ago against content hash 69f09aaadb22, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

Study-Reinforcement-Learning 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 7d 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 · 104 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.

7d ago Changed 69f09aaadb22
2mo ago First seen · 104 lines · 1,901 tokens per session scan A 6adb270b7518

Subscribe to this mod's changes

Study-Reinforcement-Learning AGENTS.md is an instructions file published in the GitHub repository 0bserver07/Study-Reinforcement-Learning (168 stars, last pushed 2d ago), with no licence file. It adds 1,901 tokens to every session, about $0.0076 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.

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Study-Reinforcement-Learning AGENTS.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
Study-Reinforcement-Learning AGENTS.md0bserver07/Study-Reinforcement-Learning	Instructions file	168	2d ago	none	A	1,901	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

Study-Reinforcement-Learning: Instructions file for Codex