skills AGENTS.md

skills AGENTS.md is an instructions file for Codex, OpenCode from cniska/skills. It costs 325 tokens per session, scanned A, original, MIT.

Project instructions for creating and maintaining reusable skills for AI coding agents. A skill is a self-contained set of instructions for handling a recurring kind of work.

In plain words
What is it for?
Use them when authoring or updating a skill, validating its files, testing it on different repositories, or preparing it for publication.
Why use it?
They provide consistent requirements for skill names, descriptions, structure, validation, testing, and references between skills.

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/cniska/skills/agents-md
Clone the repo
git clone --depth 1 https://github.com/cniska/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.

agentmods badge for skills AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/cniska/skills/agents-md.svg)](https://agentmods.dev/instructions/cniska/skills/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/cniska/skills/agents-md"><img src="https://agentmods.dev/badge/instructions/cniska/skills/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 325 This file is loaded in full into every session.
When invoked 325 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 $0.00325 $0.00325
Opus 5 $0.00162 $0.00162
Sonnet 5 $0.00065 $0.00065
Haiku 4.5 $0.00032 $0.00032

Measured 3d ago against content hash 5929feca2a96, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

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 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 · 24 lines

What it actually says

Skills

Self-contained engineering skills for AI coding agents — one per file at skills/<name>/SKILL.md. README.md is the reference for the full set, capability tiers, and principles.

Authoring a skill

  • Frontmatter name matches the directory; description starts with an imperative verb and states when to use the skill.
  • Self-contained: depend on nothing outside the skill's own directory, and reference other skills by bare name in ## See also, never by path — npx skills add copies only that directory.
  • End with a ## Red flags section (never ## Anti-patterns); keep the body terse and imperative.
  • Name capability tiers (fast / balanced / powerful), never specific models.
  • The validator enforces the mechanical rules — frontmatter, ## Red flags, no cross-directory links.
  • Add guidance only for friction that repeats in real use; prefer trimming to growing.
  • After a material change to a skill, dry-run it on unlike real repos (the skill-test skill) before pushing.

Workflow

  • New skill: make new-skill NAME=<kebab-case> DESC="<imperative description>" (or copy SKILL_TEMPLATE.md).
  • Validate: make validate. Test: make test.

Commits

  • Commit directly to main — no branch or PR.
  • Conventional Commits type(scope): description; single-line subject, no body, ASCII, aim under 50 characters and never over 72.
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 · 24 lines · 325 tokens per session scan A 5929feca2a96

Subscribe to this mod's changes

skills AGENTS.md is an instructions file published in the GitHub repository cniska/skills (5 stars, last pushed 5d ago), licensed MIT. It adds 325 tokens to every session, about $0.0016 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 2026-08-31.

Related

Other instructions, from other repositories

vscode buildNext.instructions.md

Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).

microsoft/vscode · 6,785 tokens

spec-kit AGENTS.md

AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.

github/spec-kit · 7,104 tokens

codex AGENTS.md

AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.

openai/codex · 5,182 tokens

langchain AGENTS.md

AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.

langchain-ai/langchain · 4,345 tokens

vscode oss-third-party-notices.instructions.md

Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).

microsoft/vscode · 5,001 tokens

next.js AGENTS.md

Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.

vercel/next.js · 7,296 tokens