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Wiki Lint

CommunityPopular
AgriciDaniel
wiki-lint

Run a deterministic, read-only health check on an Obsidian wiki. Use for lint, vault health check, audit wiki health, find orphans, find dead links, frontmatter audit, provenance audit, or wiki audit. Reports graph, link, frontmatter, provenance-ledger, empty-section, and stale-index findings; it does not reason broadly or repair files.

Overview

PublisherAgriciDaniel
Repositoryclaude-obsidian
Skill namewiki-lint
Stars
15K
Forks
1.5K
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 AgriciDaniel on GitHub. Read the source before you install it.

Installation

Install the Wiki 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.
  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/AgriciDaniel/claude-obsidian.git /tmp/claude-obsidian
mkdir -p .claude/skills
cp -r /tmp/claude-obsidian/skills/wiki-lint .claude/skills/wiki-lint
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wiki 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 Wiki 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 Wiki 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 wiki

Use the portable lint engine as the source of truth. Lint observes vault state; it does not create reports, dashboards, canvases, stubs, or fixes.

Resolve the installed product root from this skill's own location, not from the vault or current working directory:

bash
PRODUCT_ROOT=/absolute/path/to/installed/claude-obsidian
CORE="$PRODUCT_ROOT/scripts/claude-obsidian.py"
test -f "$CORE"

Every ../wiki/references/ link in this file resolves the same way, relative to this skill's own directory under $PRODUCT_ROOT, never relative to the selected vault's wiki/ directory.

Run

Resolve the user vault, then run one of:

bash
python3 "$CORE" lint --vault "$VAULT"
python3 "$CORE" lint --vault "$VAULT" --format markdown
python3 "$CORE" lint --vault "$VAULT" --exclude "wiki/scratchpad/*"

The repeatable --exclude GLOB flag scopes a path (for example a scratchpad folder) out of page, link-resolution, orphan, frontmatter, empty-section, and stale-index scanning.

Use --strict only when a nonzero exit for findings is useful in automation. The command remains read-only either way.

The deterministic parser understands Obsidian wikilinks and embeds, Markdown links, aliases, heading and block fragments, escaped aliases, and code fences. It skips dot-prefixed directories by default, mirroring Obsidian's own indexer. Link resolution honors .gitignore files inside the vault (no git subprocess): when a link is ambiguous between a page and a gitignored file such as a build artifact, the gitignored candidate is dropped. It reports such categories as dead or ambiguous links, orphan pages, required frontmatter gaps (including title), empty sections, stale index entries, and source/claim ledger contract violations. Report only the checks and counts present in its output; do not claim that it performed semantic, stylistic, or prose-level contradiction analysis when it did not.

Explain findings

  1. Preserve the engine's paths, line numbers, targets, categories, and counts.
  2. Group findings by likely impact: broken navigation, ambiguous resolution, metadata quality, then maintainability.
  3. Explain that an orphan may be intentional and an ambiguous basename needs a path-qualified link; do not infer intent from the finding alone.
  4. Treat allowlisted findings as policy, not as proof that the target exists.
  5. Separate deterministic facts from suggested remediation.

Do not write the Markdown rendering into the vault. Return it in chat or stdout.

Repair is a separate operation

Never auto-fix a lint result. After the user chooses specific findings to repair:

  1. Re-read each target and record its expected SHA-256.
  2. Draft only the selected changes; do not delete or merge pages without explicit consent.
  3. Build one repair bundle with a new operation ID.
  4. Inspect the bundle and show exact changed paths.
  5. Apply only after that separate review.
  6. Re-run lint read-only and compare the relevant findings.

Follow the operation transaction contract. Lint itself never applies that transaction and never commits Git.

Checkpoint

Observe the deterministic report, think about root causes rather than finding count, verify proposed repairs against current hashes, and grow by improving the workflow that produced repeated findings.

Frequently asked questions

What does the Wiki Lint AI skill do?

Run a deterministic, read-only health check on an Obsidian wiki. Use for lint, vault health check, audit wiki health, find orphans, find dead links, frontmatter audit, provenance audit, or wiki audit. Reports graph, link, frontmatter, provenance-ledger, empty-section, and stale-index findings; it does not reason broadly or repair files.

Why use Wiki Lint on TypingMind?

Because you install it once and use it with any model. Wiki 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 Wiki Lint in TypingMind?

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

Which AI models can use Wiki 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 Wiki Lint?

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

Is the Wiki Lint AI skill free?

Yes. It is published on GitHub by AgriciDaniel 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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