What is self-learning-skills AGENTS.md?

A set of instructions for skills that let a coding agent improve its guidance from its work over time. It explains how skills are discovered, when they apply, and what to do before and after a task.

Use it to manage skill discovery, follow the required pre-task checks, and apply the self-learning policy during coding work.

It gives the agent a consistent process for finding the right instructions and recording useful lessons. This helps avoid applying the wrong skill or overlooking project guidance.

How scottfalconer/self-learning-skills configures Codex and OpenCode

Reuse

Borrowing it

Nothing to install: this file belongs to scottfalconer/self-learning-skills. 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/scottfalconer/self-learning-skills/main/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/scottfalconer/self-learning-skills

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/scottfalconer/self-learning-skills/agents-md/github.svg)](https://agentmods.dev/instructions/scottfalconer/self-learning-skills/agents-md)

Your own site

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

Per session 563 This file is loaded in full into every session.

When invoked 563 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	$0.00563	$0.00563
Opus 5.5	$0.00225	$0.00225
Sonnet 5.5	$0.00113	$0.00113
Haiku 4.5	$0.00056	$0.00056

Measured 2mo ago against content hash 5b1106272df7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

self-learning-skills 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 · 40 lines

How it starts

The opening of the file, as written. The whole thing — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Instructions

Skills

Skills are discovered at startup from multiple local sources. Each entry includes a name, description, and file path so you can open the source for full instructions.

Discovery: Available skills are listed in project docs and may also appear in a runtime "## Skills" section (name + description + file path). These are the sources of truth; skill bodies live on disk at the listed paths.

Trigger rules: If the user names a skill (with $SkillName or plain text) OR the task clearly matches a skill's description, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.

Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.

How to use a skill (progressive disclosure):

After deciding to use a skill, open its SKILL.md. Read only enough to follow the workflow.
If SKILL.md points to extra folders such as references/, load only the specific files needed for the request; don't bulk-load everything.
If scripts/ exist, prefer running or patching them instead of retyping large code blocks.
If assets/ or templates exist, reuse them instead of recreating from scratch.

Description as trigger: The YAML description in SKILL.md is the primary trigger signal; rely on it to decide applicability. If unsure, ask a brief clarification before proceeding.

Coordination and sequencing:

If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.
Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.

Context hygiene:

Keep context small: summarize long sections instead of pasting them; only load extra files when needed.
Avoid deeply nested references; prefer one-hop files explicitly linked from SKILL.md.
When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.

Read the full file on GitHub · 40 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 · 40 lines · 563 tokens per session scan A 5b1106272df7

Subscribe to this mod's changes

self-learning-skills AGENTS.md is an instructions file published in the GitHub repository scottfalconer/self-learning-skills (47 stars, last pushed 19d ago), licensed MIT. It adds 563 tokens to every session, about $0.0023 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

self-learning-skills AGENTS.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
self-learning-skills AGENTS.mdscottfalconer/self-learning-skills	Instructions file	47	19d ago	MIT	A	563	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

self-learning-skills: Instructions file for Codex