Borrowing it
Nothing to install: this file belongs to Enterwell/agent-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.
curl -O https://raw.githubusercontent.com/Enterwell/agent-skills/main/AGENTS.mdgit clone --depth 1 https://github.com/Enterwell/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/enterwell/agent-skills/agents-md)<a href="https://agentmods.dev/instructions/enterwell/agent-skills/agents-md"><img src="https://agentmods.dev/badge/instructions/enterwell/agent-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.
<a href="https://agentmods.dev/instructions/enterwell/agent-skills/agents-md"><img src="https://agentmods.dev/badge/instructions/enterwell/agent-skills/agents-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00805 | $0.00805 |
| Opus 5.5 | $0.00322 | $0.00322 |
| Sonnet 5.5 | $0.00161 | $0.00161 |
| Haiku 4.5 | $0.00081 | $0.00081 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Project overview
This repository contains Enterwell's reusable AI agent skills. Each skill is a self-contained Markdown instruction file using the Agent Skills format.
The repository is documentation-oriented: skills are stored as Markdown files with YAML frontmatter, and there is no application runtime, package manager, build system, or test framework currently defined.
Repository layout
README.md- repository overview, skill format documentation, and the canonical list of available skills.skills/- root directory for all reusable skills.skills/<skill-name>/SKILL.md- one skill per directory, with YAML frontmatter followed by Markdown instructions.LICENSE- MIT license for the repository.
Setup and installation
No dependency installation is required for the current repository contents.
Development commands
No build, run, lint, format, or code-generation commands are currently defined in repository files.
When adding tooling in the future, document the exact commands in both README.md when user-facing and this file when agent-facing.
Testing instructions
No automated tests or test framework are currently defined.
For documentation-only changes, manually review changed Markdown for correctness, links, formatting, and consistency with the Agent Skills format.
Code style and conventions
- Keep each skill in its own directory under
skills/. - Name skill directories with lowercase kebab-case, matching the
namefield inSKILL.md. - Each skill must define
SKILL.md. SKILL.mdfiles should start with YAML frontmatter containing at least the skill name, description, compatibility, license, and metadata such as author and version when applicable.- Keep skill instructions practical, concise, and agent-facing.
- Avoid inventing unsupported commands, repository structure, or behavior in skill documentation.
Architecture notes
The repository is intentionally flat:
README.mddocuments the collection and lists available skills.skills/contains the skill implementations.- A skill's
SKILL.mdis the source of truth for how and when that skill should be used.
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 · 87 lines · 805 tokens per session scan A f567318d06f2
agent-skills AGENTS.md is an instructions file published in the GitHub repository Enterwell/agent-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 805 tokens to every session, about $0.0032 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 2026-08-31.
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).
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.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
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.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).