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.
git clone --depth 1 https://github.com/vouchdev/vouchWrote 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/commands/vouchdev/vouch/vouch-ask)<a href="https://agentmods.dev/commands/vouchdev/vouch/vouch-ask"><img src="https://agentmods.dev/badge/commands/vouchdev/vouch/vouch-ask/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/commands/vouchdev/vouch/vouch-ask"><img src="https://agentmods.dev/badge/commands/vouchdev/vouch/vouch-ask.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 | $0.00015 | $0.00245 |
| Opus 5.5 | $0.00006 | $0.00098 |
| Sonnet 5.5 | $0.00003 | $0.00049 |
| Haiku 4.5 | $0.00002 | $0.00024 |
Grade A, and why
vouch-ask scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
/vouch-ask
Answer "$ARGUMENTS" using only reviewed knowledge from the vouch KB. Every
statement in the answer must carry a [claim-id] or [source-id] citation.
Steps:
- Call
kb_searchwithquery: "$ARGUMENTS", thenkb_contexton the same query to assemble the working set. - If the results answer the question, write the answer citing every claim id
you relied on. Use
kb_read_pagefor typed record detail (contacts, project records, followups). - If the KB cannot support an answer, say so plainly and list the closest claims found. Do not fill gaps from your own knowledge — an uncited answer is worse than no answer.
- Only when the user explicitly asks about in-flight knowledge, list
kb_list_pendingitems — each labeledUNREVIEWED— after the cited answer, never mixed into it.
Never call kb_approve. Never restate pending proposals as facts.
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.
- 2mo ago First seen · 25 lines · 15 tokens per session scan A b74107e9c5bb
vouch-ask is a command published in the GitHub repository vouchdev/vouch (64 stars, last pushed 2mo ago), licensed MIT. It adds 15 tokens to every session and 245 once invoked, about $0.0001 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.
Other commands, from other repositories
reflect
Deep reflection. Creates journal entry.
memory-gc
Inspect or rotate hunt-memory JSONL files (audit.jsonl, patterns.jsonl, journal.jsonl). Caps file size and keeps N rotated backups so memory does not grow unbounded.
pickup
Pick up a previous hunt on a target — shows hunt history, untested endpoints, and memory-informed suggestions. Usage: /pickup target.com.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.