| name | wiki-read |
| description | Search and query the wiki — get cited answers, with automatic research when knowledge is missing. Three depth modes. Use when: 'check wiki', 'what do we know about', 'look up', 'find in wiki', 'search wiki', 'search for', 'find information about', 'do we have notes on', 'wiki context', 'existing knowledge', 'research', 'look into', 'find out about', 'investigate', 'what is', 'how does X work'. |
Wiki Read
Ask the wiki a question and get a cited answer. If the wiki doesn't have the answer, automatically researches using whatever tools are available, ingests the results, and answers from the new pages.
Resolve .wiki/ from plugin install scope. If not found, say "No wiki found. Use /wiki-write to create one."
Arguments
/wiki-read <question> — standard: search wiki first, research if not found, answer with citations/wiki-read quick <question> — index scan only, no research fallback (fastest)/wiki-read deep <question> — full wiki search + raw sources + automatic multi-channel research if needed (most thorough)
Process
Launch the wiki-reader agent with the question and depth level.
Standard depth (default)
- Read
.wiki/index.md, identify 2-4 relevant pages
- Use
bin/search-fulltext.py for ranked results
- Read the relevant pages, synthesize a cited answer with
[[slug]] references
- If NOT found or insufficient: automatically research using whatever tools are available:
- Discover available tools at runtime (WebSearch, WebFetch,
wiki_wikipedia_search for factual/encyclopedic topics, any MCP tools like Perplexity, Context7, etc.)
- Search using available tools, fetch and extract content
- Ingest results via
wiki-writer agent (mode: ingest)
- Answer from the newly created pages with
[[slug]] citations
- Note: "Researched fresh and saved to wiki."
- Offer to save analysis as a wiki page if the answer is substantial
Quick depth
- Read
.wiki/index.md only
- Scan for matching slugs/titles by text match
- Return: list of relevant pages with one-line descriptions
- No page content read, no research fallback — fastest possible response
- If not found, suggest running standard
/wiki-read
Deep depth
Everything in standard, plus:
- Search
.wiki/raw/ for source materials matching the query
- Cross-reference raw sources with compiled pages
- Use all available tools iteratively for multi-channel research if needed
- Most thorough — uses the most context
Tool Discovery
This skill works with whatever tools the user has. No hardcoded channels or services.
Available tools are discovered at runtime:
WebSearch / WebFetch — Claude Code built-in web search and fetch- Any MCP search tools (Perplexity, Exa, Tavily, etc.)
bin/search-academic.py — Semantic Scholar, arXiv, OpenAlex, CrossRef (if available)bin/search-code.py — GitHub, npm, PyPI, Stack Overflow (if available)bin/fetch.py — content extraction chain
The skill uses whatever is available — if the user has Perplexity MCP, it gets used. If they only have WebSearch, that works too.
