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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.

Install / Use

npx skills add AgriciDaniel/claude-obsidian --skill wiki-lint

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

90/100

Category

Design

Supported Platforms

Universal

Tags

Our assessment of wiki-lint

wiki-lint scores 90/100 on our quality scale, 58th of 196 Design skills we index (top 30%).

Its SKILL.md is 3.7 KB long, split into 5 sections with 2 code examples: a solid amount of guidance for an agent.

With 15,217 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
16/20
Description
15/15
Adoption
18/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 17 days ago, so wiki-lint is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

wiki-lint compared with similar skills

All 4 of these similar skills score higher than wiki-lint; compare them before choosing.

SkillScoreStarsUpdatedFormat
wiki-lint (this skill)by AgriciDaniel9015.2k17d agoSKILL.md
algorithmic-artby anthropics100177.9k5d agoSKILL.md
pptxby anthropics100177.9k5d agoSKILL.md
designby nextlevelbuilder100130.2k6d agoSKILL.md
ui-ux-pro-maxby nextlevelbuilder100130.2k6d agoSKILL.md

Frequently asked questions

How do I install wiki-lint?
Run npx skills add AgriciDaniel/claude-obsidian --skill wiki-lint. The install tabs above show the steps for each supported agent.
Which AI agents does wiki-lint work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is wiki-lint safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is wiki-lint still maintained?
The repository was last updated 17 days ago, so wiki-lint is actively maintained.

name: wiki-lint description: "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."

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:

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:

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.

Related Skills

View on GitHub
GitHub Stars15.2k
CategoryDesign
Updated17d ago
Forks1.5k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions