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 skills add OpenHands/extensions --skill setup-agents-mdgit clone --depth 1 https://github.com/OpenHands/extensionsWrote 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/skills/openhands/extensions/setup-agents-md)<a href="https://agentmods.dev/skills/openhands/extensions/setup-agents-md"><img src="https://agentmods.dev/badge/skills/openhands/extensions/setup-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/skills/openhands/extensions/setup-agents-md"><img src="https://agentmods.dev/badge/skills/openhands/extensions/setup-agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00076 | $0.01370 |
| Opus 5.5 | $0.00030 | $0.00548 |
| Sonnet 5.5 | $0.00015 | $0.00274 |
| Haiku 4.5 | $0.00008 | $0.00137 |
Grade A, and why
setup-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 1mo 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate AGENTS.md
Create a repo-specific AGENTS.md that gives AI agents the context they need to work effectively. Every section should reference real commands, real paths, and real conventions from the repository — not generic advice.
Why this matters
An AGENTS.md is the single highest-impact addition for agent readiness. It directly addresses features across multiple pillars:
- Agent Instructions: agent instruction file, README with build/run/test, contributing guide, environment variable documentation
- Feedback Loops: test run documentation — agents need exact commands
- Policy & Governance: guardrails the agent must follow
Without it, agents guess at build commands, miss project conventions, run the wrong test suite, and don't know what's dangerous. The best AGENTS.md files share the same core pattern: real commands, clear structure, explicit boundaries.
How to run
Step 0: Check for an existing AGENTS.md
Look for an existing AGENTS.md (or .agents/AGENTS.md) in the repo root.
If one exists, do not rewrite it from scratch. Instead, read the repo
(Step 1), compare what you find against what's already documented, and suggest
specific additions or changes. Present the suggestions to the user and let them
decide what to incorporate.
If no file exists, proceed to create one.
Step 1: Read the repo
Before writing anything, gather the actual information. Check these sources:
Commands (most important — agents need to know how to build, test, lint):
Makefile/justfile/Taskfile.yml— look for build/test/lint/format targetspackage.jsonscripts— npm/yarn/pnpm run targetspyproject.toml[tool.prek]/[tool.pytest]— Python tooling config.github/workflows/*.yml— CI steps reveal the real commandsCargo.toml— Rust build/test commandsbuild.gradle/pom.xml— Java/Kotlin build commandsRakefile— Ruby task definitionsdocker-compose.yml— service orchestration commands
Project structure:
- Top-level directory listing — what's in each major directory
- Monorepo indicators: workspace configs, multiple package.json/Cargo.toml/pyproject.toml
- Source vs test layout (where does code live, where do tests live)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 151 lines · 76 tokens per session scan A 33abece9c9e2
setup-agents-md is a skill published in the GitHub repository OpenHands/extensions (167 stars, last pushed today), licensed MIT. It adds 76 tokens to every session and 1,370 once invoked, about $0.0003 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.
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