richfrem/obsidian-wiki-linter

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| | Missing Concepts | Topics implied by existing articles but not yet written | | Stale Articles | Pages with vague, outdated, or thin content | | Connection Candidates | Concept pairs that should have wikilinks but don't | | New Article Suggestions | Topics the wiki should cover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:

1. Inconsistencies — conflicting claims between articles
2. Missing Concepts — implied but not yet written
3. Stale or Weak Articles — need richer content
4. Connection Candidates — wikilinks to add
5. 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-as outputs 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 orchestrator
• audit.py — structural coverage checker (complementary)
• distill_wiki.py — shares engine detection logic