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 arcasilesgroup/ai-engineering --skill ai-agents-mdgit clone --depth 1 https://github.com/arcasilesgroup/ai-engineeringWrote 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/arcasilesgroup/ai-engineering/ai-agents-md)<a href="https://agentmods.dev/skills/arcasilesgroup/ai-engineering/ai-agents-md"><img src="https://agentmods.dev/badge/skills/arcasilesgroup/ai-engineering/ai-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/arcasilesgroup/ai-engineering/ai-agents-md"><img src="https://agentmods.dev/badge/skills/arcasilesgroup/ai-engineering/ai-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 | $0.00245 | $0.02440 |
| Opus 5.5 | $0.00098 | $0.00976 |
| Sonnet 5.5 | $0.00049 | $0.00488 |
| Haiku 4.5 | $0.00024 | $0.00244 |
Grade A, and why
ai-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 16d 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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md for this repository, sized to its shape
AGENTS.md is the file coding agents read before working in a repo (https://agents.md/ and
https://github.com/agentsmd/agents.md). It is instructions for the agent, in the open, owned
by the team. ai-engineering governs the format; your repo owns the content.
One file or many
The default is ONE AGENTS.md at the repository root: most agents read the nearest file up
the tree, so a single root file covers every package. Add nested files only when a
subproject genuinely needs different instructions — monorepos where packages have different
toolchains, test runners, or review rules. The test is mechanical:
- One toolchain, one test command repo-wide → root only.
- Two or more packages with different commands, lint rules, or conventions → one root file with what is shared, one nested file per divergent package with what differs.
- A nested file must not repeat its parents: repetition drifts. State only the delta.
Say the decision out loud when you write the file: "single root AGENTS.md" or "root + N nested, one per package that diverges".
What goes in (and what never does)
Sections that earn their place, in this order when present:
- Security — hook-skip and linter-silence prohibitions, secrets/personal-data rules.
- Code style — only the rules the linter cannot check (the linter checks its own).
- Build and test commands — the exact commands, detected from the tree (package.json scripts, Cargo.toml, go.mod, pyproject.toml...), never from memory.
- Project config — short fill-in (domain, roles, paths, commands, URLs, sign-in, do-not-touch paths, context the code cannot tell; n/a when absent).
- Architecture rules — lines the critic treats as blockers.
- Shared helpers — codegraph for call chains and other project helpers.
- Git workflow — commit-as-you-go on feat/, explicit paths, no --no-verify, no push unless asked.
- Workflow — the definition of done: green gate before "done", status conventions, the verification floor (never weaken a test, an assertion or a type to make a check pass), and scope discipline (an unrelated find is reported as "noticed, not fixed").
- Unattended runs — a session with no human watching: no mid-run questions (pick the
careful reading, record the assumption, continue), the full-suite baseline before the
first edit, and hang-proof commands (non-interactive flags,
CI=true, timeouts on network calls, servers in the background). Drop the section when the repo never runs long unattended work. - Pull requests — title format, pre-commit checks, test expectations.
- Session hygiene — context-economy conventions the repo expects.
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.
- 16d ago Changed · +12 lines f0573309a3be
- 19d ago Changed · +4 lines · +1 tokens per session 5be2251cb74a
- 22d ago Changed · -5 lines 812d3f459c54
- 1mo ago Changed 13c95915a98f
- 1mo ago First seen · 156 lines · 244 tokens per session scan A ebe76e6110d3
ai-agents-md is a skill published in the GitHub repository arcasilesgroup/ai-engineering (61 stars, last pushed 2d ago), licensed Apache-2.0. It adds 245 tokens to every session and 2,440 once invoked, about $0.0010 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 2026-09-12.
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