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/testingWrote 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/testing)<a href="https://agentmods.dev/skills/garrytan/gbrain/testing"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/testing/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/testing"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/testing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- 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 | $0.00063 | $0.02208 |
| Opus 5.5 | $0.00025 | $0.00883 |
| Sonnet 5.5 | $0.00013 | $0.00442 |
| Haiku 4.5 | $0.00006 | $0.00221 |
Grade A, and why
testing 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 14d 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 — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Testing Skill — Validation + Daily Health & Regression Intelligence
Convention: see conventions/quality.md for the test-before-bulk pattern; this skill enforces it across the project's own test suite.
Two modes
This skill has two related but distinct modes:
-
Skill conformance validation — gbrain's own conformance bar (the original 1.0 scope). Validates every skill has SKILL.md with frontmatter, every reference exists, manifest + resolver coverage round-trips.
-
Project test-suite health (v0.25.1 extension) — runs the project's tiered test suite and produces a regression-classified report. Used by daily cron, container-restart bootstrap, and "how are the tests" prompts.
Pick the mode by trigger.
Mode 1: Skill conformance validation
Contract
This mode guarantees:
- Every skill directory has a
SKILL.mdfile - Every
SKILL.mdhas valid YAML frontmatter (name,description) - Every
SKILL.mdhas required sections pertest/skills-conformance.test.ts skills/manifest.jsonlists every skill directoryskills/RESOLVER.mdreferences every skill in the manifestopenclaw.plugin.jsonskills[]round-trips with bothopenclaw.plugin.jsonkeeps OpenClaw install-required native plugin fields (id, objectconfigSchema, andcontracts.contextEngineswhen applicable)- No MECE violations (duplicate triggers across skills)
Phases
- Walk skills directory. List all subdirs containing
SKILL.md. - Validate frontmatter. Parse YAML, check required fields.
- Validate sections. Check for the required headings.
- Check manifest. Every skill dir must be in
manifest.json. - Check resolver. Every manifest skill must have a RESOLVER row.
- Check round-trip. RESOLVER trigger ↔ frontmatter triggers.
- Report results.
Automation
bun test test/skills-conformance.test.ts test/resolver.test.ts test/openclaw-plugin-manifest.test.ts
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.
- 14d ago Changed c69fe3456aa9
- 17d ago Changed · +8 lines fdf7d9c2d9de
- 1mo ago First seen · 259 lines · 63 tokens per session scan A f1846ba7c350
testing is a skill published in the GitHub repository garrytan/gbrain (31,066 stars, last pushed today), licensed MIT. It adds 63 tokens to every session and 2,208 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 2026-09-03.
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dart-downstream-fix
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