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 skills/arcasilesgroup/ai-engineering/ai-verifynpx skills add arcasilesgroup/ai-engineering --skill ai-verifygit 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-verify)<a href="https://agentmods.dev/skills/arcasilesgroup/ai-engineering/ai-verify"><img src="https://agentmods.dev/badge/skills/arcasilesgroup/ai-engineering/ai-verify.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 | $0.00162 | $0.00959 |
| Opus 5 | $0.00081 | $0.00479 |
| Sonnet 5 | $0.00032 | $0.00192 |
| Haiku 4.5 | $0.00016 | $0.00096 |
Grade A, and why
ai-verify 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 6d 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Say what ran, and what it proved
What it produces
Two things, never mixed. A production-ready table where every ticked box carries the command that ticked it, and an acceptance table where every example carries its verdict.
Verify — the boxes
- Run the repository's own gate and its security lane — whatever CI runs them is the gate, not a recipe name. Paste the output. A summary of a gate is not a gate.
- For each of the eight production-ready boxes, write the command that proves it and the
output it gave. A box with no command beside it is
INCOMPLETE, and that is the answer, not a gap to fill in later. - A box that does not apply says
not applicableand why in the same line. Assertion 19 reads what sits beside each tick once the spec is shipped — it skips a draft entirely, which is every spec before it ships, so nothing catches a tick you have not earned except you. - Never tick a box on the strength of a run somebody described.
ai-eng spec checkpointreads receipts and says which of them is about this code; read its answer, not its age.
Validate — the examples
- Read the spec's
## Examples somebody can check.ai-eng spec show NNNprints how many Given, When and Then lines it holds and how many name a command with its output, and prints nothing when there is no such section — which is itself the answer, for sixteen of the nineteen specs here. The columns a row needs are inai-review/references/testing.md— if that reference file is missing, answerINCOMPLETErather than inventing the columns. - Run each example's command. Mark it
PASSwhen the output matches what the Then says,FAILwhen it does not, andINCOMPLETEwhen the Then names no command — which is most of them, and saying so is the point. - The undecidable example is the one that matters. An example nobody can decide is not a pass and not a failure; report it as the third thing.
- Do not repair the example. A Then that turned out to be wrong is a finding for
/ai-spec, and rewriting it here is the reader marking their own paper.
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.
- 6d ago First seen · 75 lines · 162 tokens per session scan A 36c05de1f3e0
ai-verify is a skill published in the GitHub repository arcasilesgroup/ai-engineering (54 stars, last pushed 4d ago), licensed Apache-2.0. It adds 162 tokens to every session and 959 once invoked, about $0.0008 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.
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