gbrain-advisor

name	gbrain-advisor
version	1.0.0
description	Proactive "make the most of gbrain" coaching. Runs `gbrain advisor` on a cadence and pings the user with the top high-leverage actions for their brain: version drift, pending migrations, stalled jobs, low embed coverage, setup smells, and uninstalled brain skills. Read-only; always asks before fixing.
triggers	["what should I do to get more out of gbrain","is my brain set up right","gbrain advisor","advise me on my brain","weekly brain checkup"]
tools	["advisor"]
mutating	false

gbrain Advisor

Convention: See skills/conventions/brain-first.md. This skill is the proactive voice of the brain — it tells the owner how to run it better.

Contract

This skill guarantees:

• Read-only. gbrain advisor never mutates. It computes a ranked list of actions from existing brain state.
• Print, never execute. You SHOW the user the findings and ASK before running any fix. The user owns every decision.
• Bounded nagging. On a cadence, surface only what changed or what's critical; don't repeat an ignored low-severity item every run.

When to run

• On demand when the user asks "how do I get more out of this brain?"
• On a weekly cadence via the cron recipe below (even idle brains get a "here's how to run this better" ping).

How to run it

gbrain advisor --json

Exit code is the severity gate (E2): 0 clean, 1 warn, 2 critical. The JSON payload is { version, generated_at, worst, findings: [...] }. Each finding has:

• severity — critical | warn | info
• title — one-line why-it-matters
• fix.command_argv — the exact command to fix it (a structured argv)
• fix.dispatch_id — present when the fix is safe to run via --apply

What to do with the findings

1. Read the findings, highest severity first.

2. Summarize the top 1-3 to the user in their own channel/voice. Lead with any critical item (e.g. pending migrations).

3. For each, show the fix.command_argv and ask whether to run it.

4. If they say yes and the finding has a fix.dispatch_id, you may run it locally with an explicit confirm:

   gbrain advisor --apply <dispatch_id>
   

   --apply is local-only, runs the fix as a structured argv (no shell), and confirms first. Findings without a dispatch_id are not auto-runnable — run their fix.command_argv yourself after the user agrees.

5. Never run a fix the user didn't approve.

Cron recipe (weekly checkup)

Install a weekly job via the cron-scheduler skill. Keep the prompt THIN — the job just reads this skill and runs the advisor:

• Schedule: weekly, one quiet-hours-respecting slot (e.g. Monday 09:00 local).
• Job prompt: Read skills/gbrain-advisor/SKILL.md and run gbrain advisor --json. If anything is critical or new since last run, ping me with the top items and the exact fix commands. Ask before fixing.
• Idempotent: the advisor is read-only, so a double-fire is harmless.

The advisor records a local run history, so on each fire you can tell the user what is new since last run rather than re-listing everything.

Output Format

When you surface advisor findings to the user, lead with severity and keep it scannable:

🧠 gbrain checkup — 2 things worth your attention

CRITICAL  Schema migrations are pending.
          Fix: gbrain apply-migrations --yes   (want me to run it?)

WARN      gbrain 0.44 is available (you're on 0.43).
          Fix: gbrain upgrade

• One block per finding, highest severity first.
• Always show the exact fix command and ASK before running it.
• If nothing is pressing, say so in one line ("brain looks healthy") — don't manufacture work.

Anti-Patterns

• Running a fix without asking. The advisor is read-only by contract. Never run --apply (or any fix command) without the user's explicit yes.
• Dumping the raw JSON at the user. Translate findings into their voice; lead with what matters.
• Re-nagging ignored low-severity items every run. Use the "new since last run" delta; respect the user's prior non-action.
• Treating info like critical. Only block/insist on critical findings (pending migrations). info is a gentle nudge.
• Calling the MCP advisor op for workspace install state. Over MCP the advisor returns brain-state signals only; uninstalled-skill findings are a local-CLI concern.