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 agentmods add skills/laozhong86/gbrain/querynpx skills add laozhong86/gbrain --skill querygit clone --depth 1 https://github.com/laozhong86/gbrainWrote 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/laozhong86/gbrain/query)<a href="https://agentmods.dev/skills/laozhong86/gbrain/query"><img src="https://agentmods.dev/badge/skills/laozhong86/gbrain/query.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 | $0.00021 | $0.00241 |
| Opus 5 | $0.00010 | $0.00120 |
| Sonnet 5 | $0.00004 | $0.00048 |
| Haiku 4.5 | $0.00002 | $0.00024 |
Grade A, and why
gbrain-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 4d 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.
This is a copy
100% identical to gbrain-query — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Query Skill
Strategy
- Start with
gbrain search "<query>"when the question contains names, exact terms, or acronyms. - Run
gbrain query "<question>"for semantic recall when embeddings are configured. OpenAI and OpenRouter both work. - Use
gbrain list,gbrain backlinks,gbrain timeline, andgbrain tagswhen the question is relational or date-sensitive. - Read the top candidate pages with
gbrain get <slug>before answering. - Cite slugs in the answer so the user can jump back into the brain.
Rules
- Fall back to lexical search if embeddings are missing or unhealthy.
- Prefer pages with fresher compiled truth when two answers conflict.
- If the brain does not contain the answer, say that directly.
- If the answer should become durable memory, suggest writing it back with
gbrain put.
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.
- 4d ago First seen · 27 lines · 21 tokens per session scan A 033ad2f3ea2a
gbrain-query is a skill published in the GitHub repository laozhong86/gbrain (8 stars, last pushed 5mo ago), licensed MIT. It adds 21 tokens to every session and 241 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to gbrain-query, differing in 0 lines, and is treated as a copy.
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