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-notegit 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-note)<a href="https://agentmods.dev/skills/arcasilesgroup/ai-engineering/ai-note"><img src="https://agentmods.dev/badge/skills/arcasilesgroup/ai-engineering/ai-note/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-note"><img src="https://agentmods.dev/badge/skills/arcasilesgroup/ai-engineering/ai-note.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 | $0.00146 | $0.01574 |
| Opus 5.5 | $0.00058 | $0.00630 |
| Sonnet 5.5 | $0.00029 | $0.00315 |
| Haiku 4.5 | $0.00015 | $0.00157 |
Grade A, and why
ai-note 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 27d 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ai-note — save what it cost you to find out
What it produces
A block in the repository's DECISIONS.md. One decision, one ## D-NNN block, with the sections below. Or, when the finding belongs in the docs, prose handed to ai-write. This skill creates no file of its own.
Steps
-
The bar is thirty minutes. If it took less than that to work out, it will take less than that again, and a note about it is noise that hides the ones that matter.
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Append one block. Do not rewrite an older block. The heading is the id the git floor counts:
## D-NNN: <what we do, in one line> Status: Accepted · Date: YYYY-MM-DD ### Context What forced the choice. Include `found`, `commit`, the files it describes, and `still_true_when`, so a later reader can tell if it rotted. ### Decision What we do, specific enough to check in the code. ### Consequences - What this makes easy - What this rules out ### Alternatives considered - **<Option>:** why not -
The Decision is the value. Context is why anybody will believe it.
-
Point at the evidence. The command you ran, its output, the line in the vendor's source. A note whose claim cannot be re-checked becomes folklore within a quarter.
-
If the note is a workaround, say what would remove the need for it, and where that fix would live — upstream, in our code, or in a decision somebody has to make.
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Searching:
git grepoverDECISIONS.mdis the whole query engine, and it is enough at this size. Read the header of anything you find and checkstill_true_whenbefore you act on it. -
When a note stops being true, delete it in a commit that says why. A wrong note is worse than no note, because it is trusted.
-
Persistence beyond this repository is not this skill's work and not this framework's. The note is committed markdown in the user's own repository, which is where it can be reviewed, dated and deleted; whatever memory system the host provides keeps its own copy on its own terms. A learning store inside the framework would be a second source of truth for something git already versions, and the second one is always the stale one.
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.
- 27d ago Changed · +11 lines · +2 tokens per session ce9bbc7177e4
- 1mo ago Changed 2de669eed37e
- 1mo ago Changed af40e585e516
- 1mo ago Changed · +60 lines · +8 tokens per session d9cd9f4192b0
- 1mo ago First seen · 63 lines · 136 tokens per session scan A f5858ebf1b4c
ai-note is a skill published in the GitHub repository arcasilesgroup/ai-engineering (61 stars, last pushed 5d ago), licensed Apache-2.0. It adds 146 tokens to every session and 1,574 once invoked, about $0.0006 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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