A skill for answering questions from vouch's reviewed knowledge base with citations. A knowledge base is a collection of stored project information, while citations show where each statement came from.

Searching vouch, assembling relevant reviewed claims, reading detailed records, and writing cited answers or plainly listing what is missing.

It avoids presenting unsupported information as fact when the knowledge base does not contain enough evidence.

vouch-ask — Skill by vouchdev

Install

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.

agentmods

npx agentmods add skills/vouchdev/vouch/vouch-ask

Any agent

npx skills add vouchdev/vouch --skill vouch-ask

Clone the repo

git clone --depth 1 https://github.com/vouchdev/vouch

Made for: Claude Code, Codex.

Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 252 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00020	$0.00252
Opus 5	$0.00010	$0.00126
Sonnet 5	$0.00004	$0.00050
Haiku 4.5	$0.00002	$0.00025

Measured 2d ago against content hash c0386a31f9de, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 2d 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.

adapters/openclaw/skills/vouch-ask/SKILL.md · 26 lines

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_search with query: "$ARGUMENTS", then kb_context on 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_page for 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_pending items — each labeled UNREVIEWED — after the cited answer, never mixed into it.

Never call kb_approve. Never restate pending proposals as facts.

Changes

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.

2d ago First seen · 26 lines · 20 tokens per session scan A c0386a31f9de

Subscribe to this mod's changes

vouch-ask is a skill published in the GitHub repository vouchdev/vouch (91 stars, last pushed 10d ago), licensed MIT. It adds 20 tokens to every session and 252 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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