cs-wiki-linter
Dispatched sub-agent that runs a periodic health check on an LLM Wiki vault. Runs mechanical checks via scripts (orphans, broken links, stale pages, missing frontmatter, duplicate titles, log gaps), does semantic checks (contradictions, stale claims, cross-reference gaps, concepts missing their own page), and produces a markdown report with suggested actions. Spawn weekly, after batch ingests, or when the user says "check the wiki" / "lint my wiki" / "audit the vault".
Best use case
cs-wiki-linter is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Dispatched sub-agent that runs a periodic health check on an LLM Wiki vault. Runs mechanical checks via scripts (orphans, broken links, stale pages, missing frontmatter, duplicate titles, log gaps), does semantic checks (contradictions, stale claims, cross-reference gaps, concepts missing their own page), and produces a markdown report with suggested actions. Spawn weekly, after batch ingests, or when the user says "check the wiki" / "lint my wiki" / "audit the vault".
Teams using cs-wiki-linter should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/cs-wiki-linter/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How cs-wiki-linter Compares
| Feature / Agent | cs-wiki-linter | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Dispatched sub-agent that runs a periodic health check on an LLM Wiki vault. Runs mechanical checks via scripts (orphans, broken links, stale pages, missing frontmatter, duplicate titles, log gaps), does semantic checks (contradictions, stale claims, cross-reference gaps, concepts missing their own page), and produces a markdown report with suggested actions. Spawn weekly, after batch ingests, or when the user says "check the wiki" / "lint my wiki" / "audit the vault".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
AI Agents for Coding
Browse AI agent skills for coding, debugging, testing, refactoring, code review, and developer workflows across Claude, Cursor, and Codex.
Best AI Skills for Claude
Explore the best AI skills for Claude and Claude Code across coding, research, workflow automation, documentation, and agent operations.
AI Agent for YouTube Script Writing
Find AI agent skills for YouTube script writing, video research, content outlining, and repeatable channel production workflows.
SKILL.md Source
# wiki-linter ## Role You are the wiki's auditor. You run periodic health checks and surface problems for the user to fix — contradictions, orphans, stale pages, missing cross-references, concepts lacking their own page. You do NOT silently auto-fix structural issues; you report and suggest. The user decides what to fix. You are spawned **per-lint-pass**, not as a long-running agent. ## Workflow Follow `references/lint-workflow.md`. Three passes. ### Pass 1 — Mechanical (scripts) Run both: ```bash python <plugin>/scripts/lint_wiki.py --vault . --json > /tmp/lint.json python <plugin>/scripts/graph_analyzer.py --vault . --json > /tmp/graph.json ``` Parse the JSON. Capture: - Orphans (zero inbound links) - Broken links (wikilinks pointing to non-existent pages) - Stale pages (`updated:` older than 90 days) - Missing frontmatter (pages without title/category/summary) - Duplicate titles - Log gap (no entries in 14+ days) - Connected components (more than 1 = disconnected islands) - Hubs (high-fan-out or high-fan-in pages) - Sinks (no outbound links) ### Pass 2 — Semantic (you read and think) The scripts can't catch these. You must read. **A. Contradictions.** Scan pages whose `updated:` is recent. For each, check whether it contradicts any related page. If so, add a `> ⚠️ Contradiction:` callout to both. **B. Stale claims.** For each flagged stale page, ask: has a newer source invalidated a claim? Suggest re-ingest or a new source hunt. **C. Concepts mentioned without their own page.** Grep for concept-shaped nouns that appear across 3+ pages as plain text (not wikilinks). Suggest new concept pages. **D. Cross-reference gaps.** For each recently-touched page, check if every entity/concept mentioned is a wikilink. Promote plain-text mentions to wikilinks where appropriate. **E. Index drift.** Compare `index.md` against actual wiki contents. If out of sync, suggest regeneration. ### Pass 3 — Report Produce a markdown report: ```markdown # Wiki lint — <date> **Total pages:** N **Components:** N **Last log:** <date> ## Found - ⚠️ <N> contradictions (list with wikilinks) - <N> orphan pages - <N> broken links - <N> stale pages - <N> concepts mentioned across 3+ pages without their own page - <N> pages with missing frontmatter - <other findings> ## Suggested actions 1. Investigate contradiction between [[sources/a]] and [[sources/b]] 2. Create concept page for "<name>" (mentioned in N sources) 3. Re-ingest [[sources/c]] — stale + contradicted by newer sources 4. Fix broken link in [[concepts/x]] 5. Cross-reference the N orphans (most belong under [[synthesis/overview]]) Want me to run these in order, or pick specific ones? ``` Then append a log entry: ```bash python <plugin>/scripts/append_log.py --vault . --op lint --title "<date> health check" --detail "<findings summary>" ``` ## Rules - **Report, don't silently fix.** The user decides what to change. - **Prioritize by impact.** Contradictions > broken links > orphans > stale > style issues. - **Use both scripts.** Mechanical + graph both reveal different problems. - **Suggest actions** — never just dump findings without recommendations. - **Always log the pass.** The log tracks wiki health over time. ## Red flags - Auto-fixing structural issues without asking → stop - Skipping semantic pass because "the scripts look clean" → do the read-and-think pass anyway - Reporting without suggestions → add suggestions - Not updating `log.md` → always log
Related Skills
wiki-query
Query the LLM Wiki — reads index.md first, drills into 3-10 relevant pages, synthesizes an answer with inline [[wikilink]] citations, and offers to file the answer back as a new comparison or synthesis page. Usage /wiki-query "<question>"
wiki-log
Show recent entries from the LLM Wiki log (wiki/log.md). Uses the standardized
wiki-lint
Run a health check on the LLM Wiki vault — mechanical checks (orphans, broken links, stale pages, missing frontmatter, log gap, duplicates) plus semantic checks (contradictions, cross-reference gaps, concepts missing their own page). Outputs a markdown report with suggested actions. Usage /wiki-lint [--stale-days N] [--log-gap-days N]
wiki-init
Bootstrap a fresh LLM Wiki vault with the three-layer structure, schema files, and starter templates. Usage /wiki-init <path> --topic "<topic>" [--tool all|claude-code|codex|cursor|antigravity]
wiki-ingest
Ingest a source file from raw/ into the LLM Wiki — read, discuss, write summary page, update cross-references across 5-15 pages, regenerate index, append to log. Usage /wiki-ingest <path-to-source>
llm-wiki
Use when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
cs-wiki-librarian
Dispatched sub-agent that answers queries against an LLM Wiki vault. Reads index.md first, drills into 3-10 relevant pages across categories, synthesizes an answer with inline [[wikilink]] citations, and offers to file the answer back into the wiki as a new comparison or synthesis page. Spawn when the user asks a substantive question the wiki might answer, says "what does the wiki say about X", "compare A and B across my sources", or wants to explore a topic.
cs-wiki-ingestor
Dispatched sub-agent that ingests a new source into an LLM Wiki vault. Reads the source, proposes TL;DR and key claims, identifies which entity/concept/synthesis pages will be touched, flags contradictions with existing pages, and — after user confirmation — writes the source summary, updates cross-references across 5-15 pages, regenerates the index, and appends a standardized log entry. Spawn when the user says "ingest this", "add this paper/article/book to the wiki", or drops a file into raw/.
tc
Track technical changes with structured records, a state machine, and session handoff. Usage: /tc <init|create|update|status|resume|close|export|dashboard> [args]
tc-tracker
Use when the user asks to track technical changes, create change records, manage TC lifecycles, or hand off work between AI sessions. Covers init/create/update/status/resume/close/export workflows for structured code change documentation.
karpathy-coder
Use when writing, reviewing, or committing code to enforce Karpathy's 4 coding principles — surface assumptions before coding, keep it simple, make surgical changes, define verifiable goals. Triggers on "review my diff", "check complexity", "am I overcomplicating this", "karpathy check", "before I commit", or any code quality concern where the LLM might be overcoding.
karpathy-check
Run Karpathy's 4-principle review on staged changes or the last commit. Checks complexity, diff noise, hidden assumptions, and goal verification. Usage /karpathy-check [--last-commit]