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/context-auditWrote 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/context-audit)<a href="https://agentmods.dev/skills/garrytan/gbrain/context-audit"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/context-audit/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/context-audit"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/context-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- 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 Agent Snooping · line 83 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 | $0.00161 | $0.03146 |
| Opus 5.5 | $0.00064 | $0.01258 |
| Sonnet 5.5 | $0.00032 | $0.00629 |
| Haiku 4.5 | $0.00016 | $0.00315 |
Grade A, and why
context-audit 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 13d 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 — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
context-audit — Token Hygiene for the Always-Loaded Context Stack
Convention: see conventions/brain-first.md — before running a fresh audit, check the brain for prior audit reports (
gbrain recall "context audit report") so you can compute token DRIFT since the last run and avoid re-flagging findings the user already declined.Convention: see conventions/quality.md — every finding cites its file and evidence; no unsourced claims.
What this is
Every file that loads on every turn is a per-turn tax: tokens, latency, and — past a point — instruction-following quality. Always-loaded files accrete (append-only release notes, promoted memory blocks nobody re-reads, rules restated in three files that drift into contradiction). This skill audits the whole always-loaded stack at once and returns a ranked, evidence-cited action list sorted by token savings.
It is an auditor, not a surgeon. It measures, finds, ranks, and recommends. The user (or a skill the user explicitly invokes afterward) applies changes.
Scope: what counts as "always-loaded"
Enumerate what THIS harness actually loads every turn — do not assume a fixed list. Typical stack:
| File | Role | Fix belongs in |
|---|---|---|
project CLAUDE.md / AGENTS.md |
orientation, routing, invariants | the file itself (source-editable) |
user-global CLAUDE.md |
cross-project instructions | the file itself (source-editable) |
auto-memory MEMORY.md |
promoted memory blocks | the memory store (demote/expire) |
SOUL.md, USER.md, ACCESS_POLICY.md, HEARTBEAT.md, rendered AGENTS.md |
bootstrap-rendered identity files | the interview answer bank / templates — NEVER the rendered file |
| harness system-prompt fragments (identity/tools files) | per-harness | wherever that harness sources them |
Skills, reference docs, and anything loaded on demand are OUT of scope as audit subjects — but they are the DESTINATION for skill-extraction findings (content that only matters for one workflow should move out of the always-loaded stack into a skill).
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.
- 13d ago Changed 1eeb9057d25e
- 14d ago Changed · +1 lines 50b987bd824f
- 16d ago Changed · +8 lines 9db7a31e9985
- 1mo ago Changed · +8 lines 450c7529b6d1
- 1mo ago First seen · 237 lines · 161 tokens per session scan A 6c811783349f
context-audit is a skill published in the GitHub repository garrytan/gbrain (31,034 stars, last pushed today), licensed MIT. It adds 161 tokens to every session and 3,146 once invoked, about $0.0006 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.
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