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 saadshahd/moo.md --skill elicitgit clone --depth 1 https://github.com/saadshahd/moo.mdWrote 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/saadshahd/moo.md/elicit)<a href="https://agentmods.dev/skills/saadshahd/moo.md/elicit"><img src="https://agentmods.dev/badge/skills/saadshahd/moo.md/elicit.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 | $0.00024 | $0.00273 |
| Opus 5 | $0.00012 | $0.00137 |
| Sonnet 5 | $0.00005 | $0.00055 |
| Haiku 4.5 | $0.00002 | $0.00027 |
Grade A, and why
elicit 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 today.
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.
What it actually says
Pull the held thing out sideways: offer one concrete thing the user can react to — a candidate, a contrast, a small set laid side by side. Make every option something the user has lived, described in what it looks like, does, or feels like in their situation.
One offer per turn: put it out and wait for the reaction. Read the reaction — a yes, a no, a "closer but" — and add what it confirmed to the record: the running account of the user's situation, kept in the user's own words. Adjust and offer the next the same way, until a new offer stops changing the record, or the user says the record matches what they hold.
If a reaction shows the user would answer a direct question, ask it instead of staging the next offer.
Hand back the record whole, in words the user confirmed as theirs, and name what it leaves open.
A direct question the user could answer would get it said → ask it. The user has said it, but the words admit two readings that would build different things → use clarify skill. The user is missing something already settled, not holding something unsaid → use explain skill.
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.
- today Changed · -31 lines 8b64c5835335
- 7d ago First seen · 46 lines · 24 tokens per session scan A ddea96b00212
elicit is a skill published in the GitHub repository saadshahd/moo.md (34 stars, last pushed yesterday), licensed MIT. It adds 24 tokens to every session and 273 once invoked, about $0.0001 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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