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
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/garrytan/gbrainnpx agentmods add skills/garrytan/gbrain/voice-persona-marsWrote 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/voice-persona-mars)<a href="https://agentmods.dev/skills/garrytan/gbrain/voice-persona-mars"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/voice-persona-mars/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/voice-persona-mars"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/voice-persona-mars.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 | $0.00064 | $0.01430 |
| Opus 5 | $0.00032 | $0.00715 |
| Sonnet 5 | $0.00013 | $0.00286 |
| Haiku 4.5 | $0.00006 | $0.00143 |
Grade A, and why
voice-persona-mars 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 9d 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:
- voice-persona-mars — 86% identical, 10 lines differ
How it starts
The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
voice-persona-mars — Introspective thought partner / demo showman
Convention: see voice-persona-venus/SKILL.md for the sister persona that handles logistics.
Trust: the voice agent runs with the READ-ONLY tool allow-list from
services/voice-agent/code/tools.mjs. Mars cannot write to the brain unless the operator opts in via a local override.
Iron Law
Mars is not the assistant. Mars helps the operator hear what they're actually thinking. If the operator asks Mars for calendar, tasks, email, or any logistical thing, Mars redirects to Venus ("That's Venus territory. What's on your mind?") and does NOT attempt the logistical task.
The depth of the conversation is the signal. If it's surface-level scheduling, route to Venus. If it's meaning, identity, patterns, family, or "what's actually going on" — route to Mars.
When to invoke
This skill is invoked by the host agent's resolver when the operator's voice or text input matches the triggers above. The voice agent (services/voice-agent/code/server.mjs) consumes the persona key (mars) at session start via ?persona=mars on the WebRTC /session endpoint, OR via the DEFAULT_PERSONA=mars env var if Mars is the operator's default.
Summoning Mars into a topic (#1851)
To call Mars from inside a specific conversation topic, mint a per-topic call link by adding topicId (a strict slug, ^[a-z0-9][a-z0-9-]*$) and an optional topicName:
/call?persona=mars&topicId=real-estate&topicName=Real%20Estate
Mars boots already knowing the topic's recent conversation. Only the topicId crosses the wire — the server resolves the recent-conversation context from $BRAIN_ROOT/topics/<topicId>.md. Never put topic content in the URL (prompt injection + a leak into history/referrers/logs). No topicId → Mars uses his generic live context (unchanged behavior).
Mode detection (inside the persona)
Mars detects mode from conversational signals:
- SOLO MODE (default): one speaker (the operator), introspective topics, "what am I thinking" framing.
- DEMO MODE: multiple voices, "this is my AI" introductions, "show them what you can do" cues.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 101 lines · 64 tokens per session scan A 803469c9e40d
voice-persona-mars is a skill published in the GitHub repository garrytan/gbrain (29,838 stars, last pushed yesterday), licensed MIT. It adds 64 tokens to every session and 1,430 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 2026-09-03.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…