GBrain is a memory and retrieval layer for AI agents that searches, connects, and synthesizes information from stored sources. It is used to give coding agents and autonomous agents access to knowledge beyond their current code, including shared company information with access controls. The catalogue add-ons help agents operate GBrain and connect it to agent workflows.
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 garrytan/gbrain --skill signal-detectorgit clone --depth 1 https://github.com/garrytan/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/garrytan/gbrain/signal-detector)<a href="https://agentmods.dev/skills/garrytan/gbrain/signal-detector"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/signal-detector/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/garrytan/gbrain/signal-detector"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/signal-detector.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00051 | $0.01542 |
| Opus 5 | $0.00026 | $0.00771 |
| Sonnet 5 | $0.00010 | $0.00308 |
| Haiku 4.5 | $0.00005 | $0.00154 |
Grade A, and why
signal-detector 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Signal Detector — Ambient Brain Capture
Lightweight capture pass applied to every substantive inbound message. It watches for TWO things with EQUAL priority:
- Original thinking — the user's ideas, observations, theses, frameworks
- Entity mentions — people, companies, media references
Original thinking is AT LEAST as valuable as entity extraction. Ideas are the intellectual capital. Entities are bookkeeping. Both compound over time.
Contract
This skill guarantees:
- Applies on every substantive message where the harness supports ambient routing (skips: purely operational messages, users who turned capture off)
- Spawns as a sub-agent where the harness supports it; otherwise runs the detection inline before composing the reply. Never blocking the response is the intent, not a runtime contract
- Announces itself on first fire and honors the per-user off switch
- Captures ideas with the user's EXACT phrasing (no paraphrasing)
- Detects entity mentions and creates/enriches brain pages
- Logs a one-line summary of what was captured
- Back-links all entity mentions (Iron Law)
- Citations on every fact written
Always-on is a harness-routing convention that a well-behaved agent
follows, not a mechanical guarantee; nothing in the gbrain runtime blocks
a reply if the skill never loads. On harnesses without per-message ambient
routing (Claude Code, Codex), apply this skill as an agent convention or
wire it via a prompt-submit hook. When the operator has enabled
memory.auto_writeback (off by default; gbrain config set memory.auto_writeback salient), the MCP server's initialize instructions
and the managed bootstrap instruction blocks carry the ambient-writeback
contract to the agent, and on Claude Code a Stop-hook extraction backstop
catches turns the convention missed. That is still a convention on the
agent side — server-delivered instructions plus a backstop, not a
mechanical guarantee.
Convention: See
skills/conventions/quality.mdfor Iron Law back-linking.
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.
- 7d ago Changed · +7 lines 0ffa92ceee02
- 9d ago First seen · 151 lines · 51 tokens per session scan A c85772f129b3
signal-detector is a skill published in the GitHub repository garrytan/gbrain (29,751 stars, last pushed yesterday), licensed MIT. It adds 51 tokens to every session and 1,542 once invoked, about $0.0003 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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