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.
Borrowing it
Nothing to install: this file belongs to garrytan/gbrain. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/garrytan/gbrain/master/CLAUDE.mdgit 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/instructions/garrytan/gbrain/claude-md)<a href="https://agentmods.dev/instructions/garrytan/gbrain/claude-md"><img src="https://agentmods.dev/badge/instructions/garrytan/gbrain/claude-md/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/instructions/garrytan/gbrain/claude-md"><img src="https://agentmods.dev/badge/instructions/garrytan/gbrain/claude-md.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 | $0.08628 | $0.08628 |
| Opus 5.5 | $0.03451 | $0.03451 |
| Sonnet 5.5 | $0.01726 | $0.01726 |
| Haiku 4.5 | $0.00863 | $0.00863 |
Grade A, and why
gbrain CLAUDE.md 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- GBrain CLAUDE.md — 91% identical, 796 lines differ
How it starts
The opening of the file, as written. The whole thing — 518 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
GBrain is a personal knowledge brain and GStack mod for agent platforms. Pluggable engines: PGLite (embedded Postgres via WASM, zero-config default) or Postgres + pgvector
- hybrid search in a managed Supabase instance.
gbrain initdefaults to PGLite; suggests Supabase for 1000+ files. GStack teaches agents how to code. GBrain teaches agents everything else: brain ops, signal detection, content ingestion, enrichment, cron scheduling, reports, identity, and access control.
North Star
gbrain aims to be the next Postgres for memory: the most well-tested, widest-coverage, best-for-the-most-at-the-least retrieval + agent memory system for company brains and personal AI, built to serve a billion people. Every feature and every eval is judged against this bar. "gbrain is best" is a WHOLE-SYSTEM claim — proven across the full BrainBench suite (retrieval, longmemeval, calibration, …) — not by any single feature. When scoping an eval, prove the FEATURE delivers value to gbrain users; do not waste it proving that gbrain's particular algorithm beats some other algorithm (a research bake-off, off-mission).
Two organizational axes (read this first)
GBrain knowledge is organized along two orthogonal axes. Users AND agents must understand both, or queries misroute silently.
- Brain — WHICH DATABASE. Your personal brain is
host. You can mount additional brains (team-published, each with their own DB and access policy) viagbrain mounts add(v0.19+). Routing:--brain,GBRAIN_BRAIN_ID,.gbrain-mountdotfile. - Source — WHICH REPO INSIDE THE DATABASE. A brain can hold many sources
(wiki, gstack, openclaw, essays). Slugs scope per source. Routing:
--source,GBRAIN_SOURCE,.gbrain-sourcedotfile.
Both axes follow the same 6-tier resolution pattern. Read
docs/architecture/brains-and-sources.md for topology diagrams (personal, team
mount, CEO-class with multiple team brains) and
skills/conventions/brain-routing.md for the agent-facing decision table.
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 Changed · +1 tokens per session 8fd346c4a27c
- 8d ago Changed · +18 tokens per session b084256f0af6
- 14d ago Changed · +1 lines · +3 tokens per session 4aea0efe1a4a
- 15d ago Changed · -1 lines · -23 tokens per session 6cb09eda8e95
- 20d ago Changed · -11 lines · +30 tokens per session 692f33737c3d
- 21d ago Changed · -2 lines · +4 tokens per session ed449d849a3b
- 22d ago Changed · +1 lines · +11 tokens per session 8e661ae8522c
- 25d ago Changed · -1 lines · +3 tokens per session 875d2513c7c9
- 26d ago Changed · +45 lines · +621 tokens per session 3eb6cfeed67a
- 27d ago First seen · 486 lines · 7,960 tokens per session scan A 964cccc716a0
gbrain CLAUDE.md is an instructions file published in the GitHub repository garrytan/gbrain (31,034 stars, last pushed today), licensed MIT. It adds 8,628 tokens to every session, about $0.0345 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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