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 postgres-adoptgit 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/postgres-adopt)<a href="https://agentmods.dev/skills/garrytan/gbrain/postgres-adopt"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/postgres-adopt/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/postgres-adopt"><img src="https://agentmods.dev/badge/skills/garrytan/gbrain/postgres-adopt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Privilege Escalation · line 59 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00091 | $0.02205 |
| Opus 5.5 | $0.00036 | $0.00882 |
| Sonnet 5.5 | $0.00018 | $0.00441 |
| Haiku 4.5 | $0.00009 | $0.00220 |
Grade A, and why
postgres-adopt 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 — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Postgres Adopt
The engine is the brain's foundation: PGLite is the zero-config floor, Postgres is where concurrency, multi-machine access, and 1000+ pages live. This skill answers "which one am I on?", prefers Postgres when the operator wants it, and moves data safely — never by flipping config.
Contract
This skill guarantees:
- Detection is engine-free and read-only:
gbrain engine status --jsonanswers with the database down (that is the point of the command). - Engine changes NEVER happen by editing config. A PGLite brain moves with
gbrain migrate --to postgres(alias--to supabase), which graduates it: plan first (exit 3), run only with the user's--yes --expect <plan_hash>, verify every table, then flip routing. This skill wraps it; it never reimplements it. - The target URL never appears in a command, transcript or output: it lives
in
GBRAIN_TARGET_URLand every command uses--url-env GBRAIN_TARGET_URL. - Provisioning consent is explicit: the docker rung needs
--allow-docker, creating a database on a local server needs--allow-create-db. Headless mutation of infrastructure the operator didn't opt into never happens.
Step 1 — Detect
gbrain engine status --json
Branch on the output:
effective_engine: "postgres"and (optionally)--probesays ok → report healthy, done.effective_engine: "postgres"but the probe fails → this is an ACCESS problem, not an adoption problem: route to db-repair.config_file_enginediffers fromeffective_engine→ an env URL is overriding the config file; tell the operator which one wins — the signal isdb_url_source(env:GBRAIN_DATABASE_URL/env:DATABASE_URLmeans env wins;env.noteadditionally fires when both env URLs are set or the cwd-.env shadow guard excluded one).thin_client: true→ the brain lives on a remote server; engine choices belong to that host. Stop.effective_engine: null(no brain) → Step 2.effective_engine: "pglite"with data → Step 3.- The output has a
graduationblock whosestateis notnone(in progress, interrupted, graduated or split) → Step 4.
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 169da89a1ab0
- 14d ago Changed · +1 lines 5131e2b2b8a8
- 15d ago Changed · +42 lines · +6 tokens per session 44b7d29a135c
- 16d ago Changed · +8 lines 1b4399fb449e
- 1mo ago First seen · 131 lines · 85 tokens per session scan A 4c402527bd0d
postgres-adopt is a skill published in the GitHub repository garrytan/gbrain (31,034 stars, last pushed today), licensed MIT. It adds 91 tokens to every session and 2,205 once invoked, about $0.0004 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.
Other skills, from other repositories
alloydb-basics
Manages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB Model Context Protocol (MCP) tools for automated database operations. Use when creating, configuring, or administering AlloyDB databases. Do NOT use for general PostgreSQL instances (e.g. Cloud SQL) or other GCP databases.
postgresql-table-design
Use this skill when designing or reviewing a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features.
volcengine-rds-postgresql
A tool for operating PostgreSQL databases hosted by Volcano Engine's managed database service. PostgreSQL is a relational database used to store structured application data.
analyzing-insights-across-teams
Analyze PostHog insights, dashboards, or teams beyond the current project by querying the prod Postgres replicas synced into the dogfood data warehouse (US project 2, "PostHog App + Website"). Use when asked to analyze insights across all teams or projects, another team's insights, or fleet-wide insight/dashboard…
dsql
Build with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, diagnose cluster performance, load data, and develop applications with a serverless, distributed SQL database. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL and PostgreSQL-to-DSQL schema conversion, foreign key…
polar-local-environment
This skill should be used when setting up or managing Polar local development environment with Docker.