agentleFS
mayersmargielamayersmargiela/brain-kit/skills/setup-brain/SKILL.md

setup-brain

Skill1 starsChanged 3 months agoMITView on GitHub

Interview an existing Codex, Claude Code, or CodeBuddy Code user and create or validate a private, role-aware Markdown workspace with governance, knowledge routing, project sources of truth, platform adapters, installation manifests, and safe rollback. Use when the user asks to set up, customize, install, repair, validate, or roll back a Brain Kit. Do not use this skill to install an agent application, create accounts, fix network access, or teach Obsidian basics.

4 other projects use a version of this.

Adopted by

Most recently taken up by

  • Other versions4 projects use a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 4

    1. mycelium-hq/ai-brain-starter★ 50same name
    2. Melvynx/ai-maxxing-skills★ 32same name
    3. Melvynx/ai-sprint-skills★ 16same name
    4. yuelenghan/brain-vault★ 1same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

The file

We split this skill into the rules it gives an agent

11 rules. 0 are common, 6 are distinctive, and 5 are very specific to this project.

  • 0

    Common

    Most of the 4 edited versions we read keep these.

  • 6

    Distinctive

    This author's own choices. Worth a look.

  • 5

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Read interview.md and conduct the interview in short batches.

    line 18
  2. Very specific:

    Run python skills/setup-brain/scripts/brainkit.py plan --platform <platform> --profile <profile.json> --target <folder>.

    line 25
  3. Very specific:

    Only after explicit approval, run python skills/setup-brain/scripts/brainkit.py apply --platform <platform> --profile <profile.json> …

    line 26
  4. Very specific:

    Run python skills/setup-brain/scripts/brainkit.py validate --target <folder> and report every warning.

    line 27
  5. Very specific:

    If the user requests reversal, run python skills/setup-brain/scripts/brainkit.py rollback --target <folder>.

    line 28
  6. Very specific:

    Never overwrite an existing file, including brain/install-manifest.json.

    line 32
  7. Distinctive:

    Never copy the developer's client projects, personal data, role names, memories, credentials, or absolute paths.

    line 34
  8. Distinctive:

    Never create more roles merely to make the system look professional.

    line 35
  9. Distinctive:

    Keep Skill, Knowledge, Evidence, Decision, and Project Fact separate.

    line 36
  10. Distinctive:

    Keep shared rules in AGENTS.md.

    line 41
  11. Distinctive:

    Use acceptance-tests.md for the final quality gate.

    line 55

“Common” is measured: kept by at least 6 in 10 of the 4 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Set Up Brain

Build a small workspace around the user's actual work. Do not invent a universal team and do not treat generated role files as proof of expertise.

Eligibility gate

Confirm that the user already has Codex, Claude Code, or CodeBuddy Code running and can open a local folder. If not, stop: application installation and onboarding are outside this product.

Obsidian is optional. The generated files are ordinary Markdown and JSON; Obsidian is only a viewing and linking interface.

Workflow

  1. Read interview.md and conduct the interview in short batches.
  2. Classify each answer as confirmed user fact, requested behavior, or assistant recommendation.
  3. Propose the smallest role set. Always include one coordinator. Add a specialist only when recurring work and a distinct quality test justify it.
  4. Confirm the target platform: codex, claude-code, codebuddy-code, or universal. Do not label Tencent WorkBuddy as a native target.
  5. Show the proposed roles, permissions, sensitive-data boundaries, sources of truth, platform adapters, and files before writing.
  6. Save the approved answers as a JSON profile matching profile-schema.md.
  7. From the Brain Kit root, run python skills/setup-brain/scripts/brainkit.py preflight --platform <platform> --target <folder>.
  8. Run python skills/setup-brain/scripts/brainkit.py plan --platform <platform> --profile <profile.json> --target <folder>. Present the plan and collision report.
  9. Only after explicit approval, run python skills/setup-brain/scripts/brainkit.py apply --platform <platform> --profile <profile.json> --target <folder>.
  10. Run python skills/setup-brain/scripts/brainkit.py validate --target <folder> and report every warning. A successful install is not proof that any role is trained.
  11. If the user requests reversal, run python skills/setup-brain/scripts/brainkit.py rollback --target <folder>. A partial rollback preserves changed files and the manifest for later review.

Non-negotiable boundaries

  • Never overwrite an existing file, including brain/install-manifest.json. A collision aborts apply.
  • Reject duplicate/reserved role IDs and unsafe manifest paths before any mutation.
  • Never copy the developer's client projects, personal data, role names, memories, credentials, or absolute paths.
  • Never create more roles merely to make the system look professional.
  • Keep Skill, Knowledge, Evidence, Decision, and Project Fact separate.
  • Multi-agent agreement is not evidence.
  • External messages, publication, payments, deployments, and destructive actions require task-specific approval.
  • Generated specialists begin at untrained; they advance only through sources, tests, and project validation.
  • Dynamic facts such as prices, policies, account state, and software versions require runtime verification.
  • Keep shared rules in AGENTS.md; platform adapters import or route to it rather than duplicate project facts.

Output contract

The generated workspace must let a new task answer, without reading every file:

  • Who is coordinating?
  • Which role owns this task and who challenges it?
  • What may be decided autonomously?
  • Where do project facts, evidence, knowledge, and decisions live?
  • What is untrained or unverified?
  • Which platform adapter is active?
  • What changed during installation, and how can it be rolled back?

Use acceptance-tests.md for the final quality gate.

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.