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/andrewsrigom/agent-skills/agents-mdgit clone --depth 1 https://github.com/andrewsrigom/agent-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/andrewsrigom/agent-skills/agents-md)<a href="https://agentmods.dev/instructions/andrewsrigom/agent-skills/agents-md"><img src="https://agentmods.dev/badge/instructions/andrewsrigom/agent-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 5.1 | $0.01546 | $0.01546 |
| Opus 5 | $0.00773 | $0.00773 |
| Sonnet 5 | $0.00309 | $0.00309 |
| Haiku 4.5 | $0.00155 | $0.00155 |
Grade A, and why
agent-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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Purpose
This repo stores reusable OSS skill packs. Keep it optimized for:
- clear skill routing
- easy sharing
- easy installation through
skills.sh - repeatable refreshes from current official docs
When andrewsrigom asks to "enforce" something in this repo, default to codifying it here in AGENTS.md, not by adding scripts, CI, or automation, unless explicitly requested.
Repo shape
- Group skills by technology at the repo root, for example
next-intl/orstripe/. - Each actual skill lives in its own folder and must contain a
SKILL.md. - Supporting files inside a skill should usually be limited to:
references/scripts/assets/
- Do not add extra docs inside skill folders such as
README.md,CHANGELOG.md, orQUICK_REFERENCE.md. - Reusable repo-level prompt templates belong in
.internal/prompts/.
Skill quality bar
- Use
skill-creatorguidance when creating or updating skills. - Optimize for routing quality first. Split by decision-making surface, not by arbitrary file count.
- Merge overlapping or weakly differentiated skills when one stronger skill would route more cleanly.
- Split overloaded skills when they own too many unrelated decisions.
- Keep
SKILL.mdlean. Move detailed material into targetedreferences/. - For code-facing skills, include at least one simple usage example directly in
SKILL.md. - Avoid duplicate coverage across skills.
- Keep references one level deep from
SKILL.md. Do not build deep reference chains. - The folder name and the
name:inSKILL.mdfrontmatter must match. - Every maintained skill should include a clear maintenance snapshot with:
- docs verification date
- current package or release snapshot when relevant
- Prefer an opinionated execution shape over a docs-summary shape.
- Do not add skills for advice a competent model would already produce reliably without repo-specific guidance.
- New skills should earn their place by reducing common AI failure modes, not by restating obvious setup steps.
- For implementation-facing skills, explicitly state:
- the default path
- when to deviate
- what to avoid
- how to verify the result
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.
- 5d ago First seen · 195 lines · 1,546 tokens per session scan A 7c0866655023
agent-skills AGENTS.md is an instructions file published in the GitHub repository andrewsrigom/agent-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 1,546 tokens to every session, about $0.0077 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.
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).
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.
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 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).
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.