richfrem Dependencies
Requires Python 3.8+ and at least one CLI installed: copilot, claude, or gemini.
pip install -r requirements.txt
Obsidian Wiki Linter
Status: Active Author: Richard Fremmerlid Domain: Obsidian Wiki Engine
Purpose
Performs a semantic health check over the LLM wiki — the step Karpathy calls
"linting." Unlike audit.py (which checks structural coverage: orphans, missing
summaries, broken wikilinks), this skill uses an LLM to analyze semantic quality:
contradictions, knowledge gaps, and connection opportunities that only emerge once
the wiki is large enough to have internal consistency requirements.
What It Checks
| Category | What it finds |
|---|---|
| Inconsistencies | Contradicting claims between two concept pages |
| Missing Concepts | Topics implied by existing articles but not yet written |
| Stale Articles | Pages with vague, outdated, or thin content |
| Connection Candidates | Concept pairs that should have wikilinks but don't |
| New Article Suggestions | Topics the wiki should cover based on its current scope |
Usage
Run semantic health check (default engine)
python ./scripts/lint_wiki.py --wiki-root /path/to/wiki-root
Sample more pages for larger wikis
python ./scripts/lint_wiki.py --wiki-root /path/to/wiki-root --sample 30
Force engine
python ./scripts/lint_wiki.py --wiki-root /path/to/wiki-root --engine claude
Dry run (print prompt without calling LLM)
python ./scripts/lint_wiki.py --wiki-root /path/to/wiki-root --dry-run
Engine Fallback Chain
Same strict cheap-model chain as obsidian-rlm-distiller:
1. copilot → gpt-5-mini (Paid, AI Credits)
2. claude → claude-haiku-4-5 (fallback, Paid)
3. gemini → gemini-3-flash-preview (final fallback, Paid)
Output
Report is written to {wiki-root}/meta/lint-report.md with YAML frontmatter:
generated_at: "2026-04-16T..."
engine: "claude"
model: "claude-haiku-4-5"
Followed by five sections:
- Inconsistencies — conflicting claims between articles
- Missing Concepts — implied but not yet written
- Stale or Weak Articles — need richer content
- Connection Candidates — wikilinks to add
- New Article Suggestions — fresh topics to write
When to Use
- After the wiki reaches ~20+ concept nodes (semantic quality starts to matter)
- As a weekly maintenance step before a major query session
- When you notice the wiki feels inconsistent or fragmented
- Before filing
--save-asoutputs back — lint first to know what gaps to fill - As the final step in
/wiki-rebuild(after ingest, distill, build)
Audit vs. Lint
audit.py |
lint_wiki.py |
|---|---|
| Structural: missing summaries, broken links, orphans | Semantic: contradictions, gaps, stale content |
| Always fast, no LLM needed | Requires LLM call |
Run before every /wiki-query |
Run periodically (weekly or post-rebuild) |
| Exit code 1 on critical issues | Always exits 0 (report-only) |
Related Scripts
lint_wiki.py— semantic health check orchestratoraudit.py— structural coverage checker (complementary)distill_wiki.py— shares engine detection logic