agentleFS
Sign inStart free
tonydzitonydzi/second-brain-starter-kit/skills/brain/SKILL.md

brain

Skill6 starsChanged 2 months agoMITView on GitHub

Health-check the second brain so failures are not silent: is the local search server alive, is the RAG index fresh, is the session-memory ledger filling, did the nightly distillation run. Read-only, with a green/red verdict per component. Triggers: "/brain", "/memory", "is the reindex alive".

25 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use research.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • NVIDIASkill

    research

    Before designing a feature, research how comparable libraries solve the problem, check best practices, known pitfalls, and upstream changes. Use when starting a new feature, investigating an unfamiliar area, or the user asks to research something.

    Also in 4 projects that use this

The file

Create a free account to mount
Files
SKILL.md

/brain — second-brain health at one glance

🧒 When reporting to a non-technical operator, end with a short plain-words recap (rule eli5-always).

Catches SILENT breakage of the memory/RAG stack (the things that kept breaking month after month: the reindex, the local search server, the memory pilot). Read-only, 0 tokens.

What it does (one script)

python $IMPORTS_ROOT/brain_health.py

Checks 5 things and colors them 🟢/🟡/🔴:

  1. Search server on its local port — alive or not (if it's down, auto-recall silently disappears); also shows whether the graph-assisted mode is on.
  2. Index _brain_e5.npy — how fresh (🟡 if the reindex lags >48h).
  3. TurnState ledger — how many turns recorded (memory Phase 1), when the last one was.
  4. Nightly distillation — candidates in quarantine + when the last run happened.
  5. A/B direct-vs-graph recall — how many runs + the operator's verdicts (👍/👎).

Writes a dashboard $OBSIDIAN_VAULT/_Dashboards/Brain-Health.html (the operator reads with their eyes, [[prefer-visual-dashboards]]). Exit code 0/1/2 = ok/warn/red (for scripts).

When to fix (on 🔴/🟡)

  • 🔴 search server down → run the restart script (as admin, see [[always-on-memory-pilot]]); or reboot (the at-logon task brings it up).
  • 🟡 index lagging → gpu_check.py [--kill], then brain_embed_update.py [--wait-gpu 10] ([[reindex-routine]]).
  • 🟡 ledger empty → fine if memory Phase 1 was just enabled (it fills from the next sessions on).

What it does NOT do

It doesn't fix anything and doesn't write to the vault. It's a diagnostic. Fixing is a separate explicit step (the "read before you fix" rule, [[verify-existing-before-proposing]]).

<!--kit-footer-->

Like this skill? It is one of 100 in second-brain-starter-kit: the second brain we built for ourselves and run every day at Palo Alto AI Research Lab. Install the whole set with npx skills add tonydzi/second-brain-starter-kit. Everything is open source and free, so take what you need.

Flagships worth a look on their own: secondop-panel (a second opinion from a panel of external models), claude-memory-tidy (stop your agent's memory from rotting), telegram-mcp-kit (your own Telegram over MCP in about 15 minutes).

Author: Anton Dziatkovskii, Palo Alto AI Research Lab. Telegram @tonydzi - WhatsApp +1 341 222 9178 - X @Tony_Stef_

Engineers: want to test-drive this setup? Message me. I hand out free starter seeds to engineers who test and report back, and custom skill requests are welcome.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free