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 atman-33/workhub --skill team-kb-querygit clone --depth 1 https://github.com/atman-33/workhubWrote 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/atman-33/workhub/team-kb-query)<a href="https://agentmods.dev/skills/atman-33/workhub/team-kb-query"><img src="https://agentmods.dev/badge/skills/atman-33/workhub/team-kb-query/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/atman-33/workhub/team-kb-query"><img src="https://agentmods.dev/badge/skills/atman-33/workhub/team-kb-query.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 | $0.00045 | $0.00272 |
| Opus 5.5 | $0.00018 | $0.00109 |
| Sonnet 5.5 | $0.00009 | $0.00054 |
| Haiku 4.5 | $0.00005 | $0.00027 |
Grade A, and why
team-kb-query 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 1mo 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
Query the team KB
Answer from <teamRoot>/ai/knowledge/ with citations, instead of guessing.
Steps
- Resolve the KB root from
<team-context>. - Navigate via indexes first: read
knowledge/_index.md, pick candidate topic folders, read their_index.md, then only the notes that look relevant. Fall back to Grep acrossknowledge/for specific terms. For project-specific questions also checkprojects/<p>/docs/spec/spec.mdanddocs/decisions/. - Synthesize an answer in the user's language, citing each source note by path so they can open it.
- Flag gaps: if the KB does not answer the question (or is out of
date), say so explicitly — and once the user supplies the real answer,
propose saving it with
team-kb-save.
Rules
- Read-only: this skill never modifies the KB.
- Prefer newer notes when two conflict, and surface the conflict.
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.
- 1mo ago First seen · 28 lines · 45 tokens per session scan A a9f0c5ec93cf
team-kb-query is a skill published in the GitHub repository atman-33/workhub (3 stars, last pushed 2d ago), licensed MIT. It adds 45 tokens to every session and 272 once invoked, about $0.0002 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 2026-09-03.
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