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 meeting-ingestiongit 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/meeting-ingestion)<a href="https://agentmods.dev/skills/garrytan/gbrain/meeting-ingestion"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/meeting-ingestion/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/meeting-ingestion"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/meeting-ingestion.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk warn
- 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 304 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 Agent Snooping · line 340 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.
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 | $0.00125 | $0.05700 |
| Opus 5 | $0.00063 | $0.02850 |
| Sonnet 5 | $0.00025 | $0.01140 |
| Haiku 4.5 | $0.00013 | $0.00570 |
Grade A, and why
meeting-ingestion 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 — 498 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting Ingestion Skill — Unified Pipeline
Filing rule: Read
skills/_brain-filing-rules.mdbefore creating any new page.
Convention: See
skills/conventions/quality.mdfor Iron Law back-linking, andskills/conventions/brain-first.mdfor the lookup chain — resolve every name against the brain BEFORE reaching for external lookups.
Contract
This skill guarantees:
- Works with ANY meeting recorder — AI notetaker export, webhook payload, share link, raw audio transcription, or manual paste. The normalized transcript record (below) is the contract; per-source fetch/parse is the host agent's job
- One brain page per REAL meeting — multi-meeting recordings are split first
- Meeting page created with attendees, summary, key decisions, action items, notable quotes
- Speakers resolved by evidence, never by guess
- Recorder auto-summaries treated as CLAIMS, not facts — every surprising claim passes the consistency check before it touches an entity page
- EVERY attendee gets a people page (created or updated)
- EVERY company discussed gets entity propagation
- Timeline entries on ALL mentioned entities (timeline merge)
- Back-links created bidirectionally
- Meeting is NOT fully ingested until enrich runs for every entity
- The meeting is never REPORTED as ingested until the verification checklist (below) passes — every quote grounded, every slug backed by a page and a timeline backlink, every speaker resolved or flagged
- The narrated SEQUENCE is verified independently of substance: a sequence contradiction BLOCKS ingestion until fixed or explicitly waived by the user
Every attendee and company mentioned MUST get a back-link from their page to the meeting page. An unlinked mention is a broken brain.
Any recorder, one pipeline
Meeting content arrives from many sources: an AI notetaker (Granola and Circleback are common examples), a phone voice memo, a video-call transcript export, or a transcript the user pastes directly. Do NOT build per-vendor pipelines or paraphrase this skill in ad-hoc instructions — normalize whatever the source provides into the transcript record below, then run the shared phases. Source-specific logic ends at normalization.
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.
- 12d ago First seen · 498 lines · 125 tokens per session scan A 949a491b98e7
meeting-ingestion is a skill published in the GitHub repository garrytan/gbrain (29,789 stars, last pushed 3d ago), licensed MIT. It adds 125 tokens to every session and 5,700 once invoked, about $0.0006 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.
Other skills, from other repositories
mem0-oss-to-platform
Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local Memory class) to the mem0 Platform / hosted / managed SDK (the MemoryClient class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g.…
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…
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.
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…
establishing-project-context
Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.
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.