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Second Brain Lint

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undefined-ui
second-brain-lint

Audit a second-brain vault for structural problems and repair them: broken wikilinks, orphan pages, empty stubs, frontmatter that violates the schema, near-duplicate pages, and stale index entries. Use this skill whenever the user asks to lint, clean, audit or check the health of their vault, says pages feel messy or links are broken, after a large bulk import, or when a scheduled maintenance run fires. Do NOT use for ingesting new sources, for answering questions from the vault, or for rewriting page content that is structurally fine but reads badly.

Overview

Publisherundefined-ui
Repositorysecond-brain-os
Skill namesecond-brain-lint
Stars
1K
Forks
166
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by undefined-ui on GitHub. Read the source before you install it.

Installation

Install the Second Brain Lint AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/undefined-ui/second-brain-os/tree/main/skills/second-brain-lint
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/undefined-ui/second-brain-os.git /tmp/second-brain-os
mkdir -p .claude/skills
cp -r /tmp/second-brain-os/skills/second-brain-lint .claude/skills/second-brain-lint
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Second Brain Lint in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Second Brain Lint on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Second Brain Lint is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Lint the vault

Structural rot is silent. Nothing errors, nothing crashes, the vault just slowly stops answering questions well because a third of its pages are unreachable. Linting is the only thing that catches it before the owner does.

Core rule

Report before repairing. Fix the mechanical problems automatically, but never delete or merge a page without listing it first and getting a yes, because the owner may have written it by hand.

Workflow

  1. Inventory. Count pages by type. Build the link graph by parsing every [[wikilink]].
  2. Broken links. Links pointing at pages that do not exist. Distinguish two cases: a typo or rename, which you fix, and a genuine gap, which goes into index.md under Gaps.
  3. Orphans. Pages with no inbound links. For each, either find where it should be linked from and add the link, or flag it as a candidate for deletion.
  4. Stubs. Pages under roughly 40 words with no links. Usually a failed ingest. Flag for re-ingest from the original source in raw/.
  5. Schema. Missing or malformed frontmatter, wrong type, missing dates, tags outside the existing vocabulary.
  6. Near-duplicates. Pages with very similar titles or aliases. Propose merges; do not perform them unsolicited.
  7. Index drift. Pages missing from index.md, index entries pointing nowhere.
  8. Repair, then append the run to log.md.

Output format

Vault: <n> pages (<n> sources, <n> concepts, <n> entities, <n> synthesis)
Link graph: <n> links, average <n> per page, <n> orphans

Fixed automatically:
- <list>

Needs a decision:
- <list, each with the recommended action>

Health: orphan rate <n>%, broken link rate <n>%, stub rate <n>%

Calibration

An aggressive linter that merges pages on its own judgement destroys work. A timid one that only reports produces a list nobody acts on. The split above is the useful line: mechanical fixes happen, semantic decisions get proposed.

Do not run a full lint after every ingest. Weekly, or after an import of more than about twenty sources.

Frequently asked questions

What does the Second Brain Lint AI skill do?

Audit a second-brain vault for structural problems and repair them: broken wikilinks, orphan pages, empty stubs, frontmatter that violates the schema, near-duplicate pages, and stale index entries. Use this skill whenever the user asks to lint, clean, audit or check the health of their vault, says pages feel messy or links are broken, after a large bulk import, or when a scheduled maintenance run fires. Do NOT use for ingesting new sources, for answering questions from the vault, or for rewriting page content that is structurally fine but reads badly.

Why use Second Brain Lint on TypingMind?

Because you install it once and use it with any model. Second Brain Lint is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Second Brain Lint in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/undefined-ui/second-brain-os/tree/main/skills/second-brain-lint. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Second Brain Lint?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Second Brain Lint?

As many as you like. As long as a model supports skills, you can use Second Brain Lint with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Second Brain Lint AI skill free?

Yes. It is published on GitHub by undefined-ui under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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