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.
npx agentmods add instructions/narumiruna/skills/agents-mdgit clone --depth 1 https://github.com/narumiruna/skillsWrote 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.
[](https://agentmods.dev/instructions/narumiruna/skills/agents-md)<a href="https://agentmods.dev/instructions/narumiruna/skills/agents-md"><img src="https://agentmods.dev/badge/instructions/narumiruna/skills/agents-md.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00932 | $0.00932 |
| Opus 5 | $0.00466 | $0.00466 |
| Sonnet 5 | $0.00186 | $0.00186 |
| Haiku 4.5 | $0.00093 | $0.00093 |
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 yesterday.
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.
How it starts
The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Guidelines
Follow global defaults; this file contains only repository-specific additions and overrides.
Communication & Documentation
- Lead with the most important relevant information and omit anything unnecessary or repeated.
- Use clear structure, familiar words, and concise sentences.
- Explain the main idea simply before adding necessary detail.
- Keep information accurate.
- Make documented rules specific and verifiable.
- Use
./skills/prompting-gpt/references/gpt-5.6.mdas the primary model guide when creating, revising, or reviewing skills and other agent-facing prompts. - Use GPT-5.5 only after GPT-5.6 as supplementary prompt guidance, and use any other versioned model guide only when the task targets that model version.
- Keep external positioning, installation flows, and skill discovery in
README.md, and keep maintainer workflow in this file. - Update the README catalog when a skill is added, deprecated, renamed, recategorized, or materially changes its trigger.
- Update installation documentation and executable recipes only in the files that own the affected flow.
Code Style
- Follow KISS (Keep It Simple) and YAGNI (You Aren't Gonna Need It).
- Prefer simple, minimal solutions over unnecessary complexity.
- Use lowercase kebab-case for skill directories and name every required entry file exactly
SKILL.md. - Preserve a skill's original user intent when naming or renaming it; do not force
<verb-ing>-<object>when that changes the meaning. - Retain explicit-invocation skills that provide useful mode shortcuts even when their behavior can be inferred; keep
explaining-step-by-stepactive. - Keep a skill's frontmatter description and README catalog entry aligned when its trigger or purpose changes.
- Keep examples repository-relative and executable when practical.
- For user interfaces, apply Apple-derived design philosophy across platforms while translating platform-specific metrics and controls to target conventions; minimize cognitive load without sacrificing functional completeness, keep critical actions and state visible, and use predictable progressive disclosure for secondary complexity.
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.
- yesterday Changed · -7 lines · -22 tokens per session ba6770b6320f
- 5d ago First seen · 66 lines · 954 tokens per session scan A 87a4cd1abe95
skills AGENTS.md is an instructions file published in the GitHub repository narumiruna/skills (13 stars, last pushed today), licensed MIT. It adds 932 tokens to every session, about $0.0047 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 2026-08-30.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
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.
vscode buildNext.instructions.md
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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.
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.
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).