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 gbrain-advisorgit 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/gbrain-advisor)<a href="https://agentmods.dev/skills/garrytan/gbrain/gbrain-advisor"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/gbrain-advisor/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/gbrain-advisor"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/gbrain-advisor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 81 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Excessive Agency · line 109 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00076 | $0.01369 |
| Opus 5.5 | $0.00030 | $0.00548 |
| Sonnet 5.5 | $0.00015 | $0.00274 |
| Haiku 4.5 | $0.00008 | $0.00137 |
Grade A, and why
gbrain-advisor 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 15d 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-advisor — 95% identical, 10 lines differ
How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
gbrain Advisor
Convention: See
skills/conventions/brain-first.md. This skill is the proactive voice of the brain — it tells the owner how to run it better.
Contract
This skill guarantees:
- Read-only.
gbrain advisornever mutates. It computes a ranked list of actions from existing brain state. - Print, never execute. You SHOW the user the findings and ASK before running any fix. The user owns every decision.
- Bounded nagging. On a cadence, surface only what changed or what's critical; don't repeat an ignored low-severity item every run.
When to run
- On demand when the user asks "how do I get more out of this brain?"
- On a weekly cadence via the cron recipe below (even idle brains get a "here's how to run this better" ping).
- Monthly, the advisor also surfaces the backup-coverage verdict (
gbrain backup status— which knowledge repos have no git remote); relay any warn.
How to run it
gbrain advisor --json
Exit code is the severity gate (E2): 0 clean, 1 warn, 2 critical. The JSON
payload is { version, generated_at, worst, findings: [...] }. Each finding has:
severity—critical|warn|infotitle— one-line why-it-mattersfix.command_argv— the exact command to fix it (a structured argv)fix.dispatch_id— present when the fix is safe to run via--apply
What to do with the findings
-
Read the findings, highest severity first.
-
Summarize the top 1-3 to the user in their own channel/voice. Lead with any
criticalitem (e.g. pending migrations). -
For each, show the
fix.command_argvand ask whether to run it. -
If they say yes and the finding has a
fix.dispatch_id, you may run it locally with an explicit confirm:gbrain advisor --apply <dispatch_id>--applyis local-only, runs the fix as a structured argv (no shell), and confirms first. Findings without adispatch_idare not auto-runnable — run theirfix.command_argvyourself after the user agrees. -
Never run a fix the user didn't approve.
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.
- 15d ago Changed · -9 lines c9e51d609121
- 16d ago Changed 6b085cfb83fa
- 17d ago Changed · +1 lines dd1cf3192a7b
- 18d ago Changed 0e8d4c7eef4d
- 19d ago Changed · +16 lines a5a74ab4390c
- 1mo ago First seen · 120 lines · 76 tokens per session scan A b4186ce45ba1
gbrain-advisor is a skill published in the GitHub repository garrytan/gbrain (31,098 stars, last pushed today), licensed MIT. It adds 76 tokens to every session and 1,369 once invoked, about $0.0003 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.
Other skills, from other repositories
mem0-oss-to-platform
Plan, then execute, a migration of a project from the mem0 open-source / self-hosted SDK (local Memory class) to the mem0 Platform / hosted SDK (MemoryClient). TRIGGER when: the developer wants to move, switch, or migrate mem0 off OSS/self-hosted to the hosted API, e.g. "migrate my mem0 setup to the platform", "switch…
forget
Remove a personal fact, preference, relationship detail, topic, or prior event from Muse's active memory and stop existing copies or automations from bringing it back. Use for explicit requests such as 'forget that', 'don't remember this about me', or 'remove that from your memory'. Do not use when 'forget it' merely…
Cortex
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
shellm
Reference for the shellm system — recursive LLM shell, identity management, memory, skills, trajectory, and all CLI tools. Use when working on shellm itself, debugging agent behavior, or understanding how the pieces fit together.