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wiki-lint

Run repeatable, read-only checks on an Obsidian wiki to find broken or ambiguous links, isolated pages, missing metadata, empty sections, outdated index entries, and source-record issues. Review findings with paths, line numbers, and counts.

OriginalShow the original 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.

Works withObsidian
See how to install

Good for

  • Finding broken links and isolated pages
  • Auditing note metadata and source records
  • Reviewing empty sections and outdated index entries

Files included (1)

  • SKILL.md3.7 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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.

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