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 ingestgit 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/ingest)<a href="https://agentmods.dev/skills/garrytan/gbrain/ingest"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/ingest/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/ingest"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/ingest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk warn
- 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 | $0.00017 | $0.03346 |
| Opus 5.5 | $0.00007 | $0.01338 |
| Sonnet 5.5 | $0.00003 | $0.00669 |
| Haiku 4.5 | $0.00002 | $0.00335 |
Grade A, and why
ingest 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 12d 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 — 329 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ingest Skill
Ingest meetings, articles, media, documents, and conversations into the brain.
Filing rule: Read
skills/_brain-filing-rules.mdbefore creating any new page.
Contract
- Every fact written to a brain page carries an inline
[Source: ...]citation with date and provenance. - Every entity mention creates a back-link from the entity's page to the page mentioning them (Iron Law).
- Raw sources are preserved for provenance via
gbrain files upload-rawwith automatic size routing. - State sections are rewritten with current best understanding, never appended to.
- After the user's explicit automatic-capture opt-in (see
skills/signal-detector/SKILL.md), entity detection fires on every substantive inbound message; notable entities get pages or updates. Without that opt-in, capture only what the user asks to save. - Notability gate before any new entity page: existing pages are updated, and a NEW page is created only for a notable entity and only with meaningful content from web search or existing brain context — no stubs. A non-notable mention stays an inline reference on the page that mentions it.
Convention: See
skills/conventions/quality.mdfor Iron Law back-linking.
Every mention of a person or company with a brain page MUST create a back-link
FROM that entity's page TO the page mentioning them. An unlinked mention is a
broken brain. See skills/_brain-filing-rules.md for format.
Citation Requirements (MANDATORY)
Every fact written to a brain page must carry an inline [Source: ...] citation.
- User's statements:
[Source: User, {context}, YYYY-MM-DD] - Meeting data:
[Source: Meeting "{title}", YYYY-MM-DD] - Email/message:
[Source: email from {name} re: {subject}, YYYY-MM-DD] - Web content:
[Source: {publication}, {URL}, YYYY-MM-DD] - Social media:
[Source: X/@handle, YYYY-MM-DD](URL)(include link) - Synthesis:
[Source: compiled from {sources}]
Phases
Router note: This skill is a router. For specialized ingestion, see: idea-ingest, media-ingest, meeting-ingestion.
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.
- 12d ago Changed · -10 lines c84e1605a2d2
- 13d ago Changed ec8fbf7a9da5
- 14d ago Changed · +5 lines 264f9b5a847d
- 15d ago Changed ae4da2f51b1b
- 16d ago Changed · +18 lines 8c7d931ae077
- 17d ago Changed · +4 lines 31df4c7c8eb1
- 1mo ago First seen · 312 lines · 17 tokens per session scan A dc40ecc00728
ingest is a skill published in the GitHub repository garrytan/gbrain (31,034 stars, last pushed today), licensed MIT. It adds 17 tokens to every session and 3,346 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.
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