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 idea-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/idea-ingest)<a href="https://agentmods.dev/skills/garrytan/gbrain/idea-ingest"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/idea-ingest.svg" alt="Measured on agentmods" height="20"></a>- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Excessive Agency · line 120 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 | $0.00060 | $0.01178 |
| Opus 5 | $0.00030 | $0.00589 |
| Sonnet 5 | $0.00012 | $0.00236 |
| Haiku 4.5 | $0.00006 | $0.00118 |
Grade A, and why
idea-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 8d 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Idea Ingest Skill
Filing rule: Read
skills/_brain-filing-rules.mdbefore creating any new page.
Contract
This skill guarantees:
- Every ingested item has a brain page with genuine analysis (not just a summary)
- The author gets a people page (MANDATORY for anyone whose thinking is worth ingesting)
- Cross-links created bidirectionally (source ↔ author, source ↔ mentioned entities)
- Raw source preserved for provenance via
gbrain files upload-raw - Every fact has an inline
[Source: ...]citation - Filing follows primary subject rules (not format-based)
Returns (when invoked by another skill or sub-agent):
page_path: brain page path of the ingested item (e.g.,concepts/flywheel-effects)author_path: brain page path of the author (e.g.,people/alice-example)cross_links: list of all cross-links createdstatus:ingested|updated|fetch_failed
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.
Format: - **YYYY-MM-DD** | Referenced in [page title](path) — brief context
Phases
-
Fetch the content. Use appropriate tools for the content type (web fetch for articles, API for tweets, PDF reader for documents).
-
Upload raw source. Save the fetched content for provenance:
gbrain files upload-raw <file> --page <slug> -
Identify the author — MANDATORY people page. Anyone whose thinking is worth ingesting is worth tracking.
- Search brain for existing author page
- If no page → CREATE ONE with compiled truth + timeline format
- If page exists → update timeline with this new publication
- Cross-link both directions
-
Save to brain. File by PRIMARY SUBJECT (read
skills/_brain-filing-rules.md):- About a person →
people/ - About a company →
companies/ - A reusable framework →
concepts/ - Raw data dump →
sources/
- About a person →
-
Analyze for the user. Reply with analysis that connects the content to what the brain knows. Think about:
- Active projects — is this relevant?
- Contradictions — does this challenge existing brain knowledge?
- Connections — does this involve known people/companies?
- Don't just summarize. Tell the user things they wouldn't have noticed.
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.
- 8d ago First seen · 125 lines · 60 tokens per session scan A 01ef449b7d5d
idea-ingest is a skill published in the GitHub repository garrytan/gbrain (29,668 stars, last pushed today), licensed MIT. It adds 60 tokens to every session and 1,178 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 2026-08-30.
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.