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 agentmods add skills/garrytan/gbrain/research-compendiumnpx skills add garrytan/gbrain --skill research-compendiumgit 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/research-compendium)<a href="https://agentmods.dev/skills/garrytan/gbrain/research-compendium"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/research-compendium.svg" alt="Measured on agentmods" height="20"></a>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 | $0.05528 |
| Opus 5 | $0.00063 | $0.02764 |
| Sonnet 5 | $0.00025 | $0.01106 |
| Haiku 4.5 | $0.00013 | $0.00553 |
Grade B, and why
research-compendium scanned grade B with 1 finding 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 6d 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.
Instruction-override phrasingmediumPrompt injection
Text telling the model to disregard its earlier instructions or safety rules is the shape of a prompt injection, whoever wrote it.
"ignore previous instructions," embedded tool-call syntax, or urgent demands Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
How it starts
The opening of the file, as written. The whole thing — 433 lines — stays where its author put it; the contents beside it link to each section on GitHub.
research-compendium — Archive Everything, Summarize 1:1, Synthesize Once
Convention: see conventions/brain-first.md for the lookup chain. Phase 1 is literally brain-first: search the brain before the open web — the corpus may already be partly ingested.
Convention: see conventions/quality.md for citation rules, quote fidelity, and back-link enforcement.
Convention: see _brain-filing-rules.md — everything this skill writes files under
research/per the research rule.
What this is
Turn a research question into a permanent brain asset: find everything → archive every primary source → summarize each 1:1 → synthesize one self-contained compendium.
This is distinct from data-research (which extracts structured data into
trackers). This skill produces prose knowledge synthesis — a definitive,
fast-to-read, comprehensive reference page backed by an archived source corpus.
Use when the user says "research X, read everything, save the sources,
summarize each, and write me a compendium / definitive guide /
everything-you-need-to-know doc." If the ask is structured data into a
table/tracker → data-research instead.
Retention policy (read before archiving)
Archive-everything is gated by the user's privacy posture — minimization is a feature. Verbatim archiving is the default for public research corpora (papers, standards, published articles). When a source is personal, sensitive, or third-party-private (correspondence, medical or financial records, private group content), or when the user has expressed a minimization preference: store the citation + a summary, skip the verbatim mirror, and say so in the index. A compendium that hoards sensitive raw material the user never wanted retained is a bug, not thoroughness.
Untrusted content
Convention: see conventions/untrusted-content.md — the canonical home for this rule. This section is the verbatim-archive expansion; the shared convention carries the cross-skill canon.
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.
- 6d ago First seen · 433 lines · 125 tokens per session scan B 3394628692d6
research-compendium is a skill published in the GitHub repository garrytan/gbrain (29,591 stars, last pushed 2d ago), licensed MIT. It adds 125 tokens to every session and 5,528 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it B with 1 finding (instruction-override phrasing). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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