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Wiki Query

OrganizationPopular
paperclipai
wiki-query

Use when an LLM Wiki operation issue asks a question. Answer from wiki pages and raw sources with citations, name gaps plainly, and offer to file durable synthesis when the answer should compound.

Overview

Publisherpaperclipai
Repositorypaperclip
Skill namewiki-query
Stars
95.4K
Forks
16.2K
Bundled files
Instructions only
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by paperclipai on GitHub. Read the source before you install it.

Installation

Install the Wiki Query AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/paperclipai/paperclip/tree/master/packages/plugins/plugin-llm-wiki/skills/wiki-query
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/paperclipai/paperclip.git /tmp/paperclip
mkdir -p .claude/skills
cp -r /tmp/paperclip/packages/plugins/plugin-llm-wiki/skills/wiki-query .claude/skills/wiki-query
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wiki Query in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Wiki Query on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Wiki Query is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Wiki Query

Answer a question from what the wiki actually contains, with citations.

Inputs

  • An operation issue with operationType: "query" and the question in the body.
  • The operation issue's target wikiId, spaceSlug, and space root.

Workflow

  1. Open the target space's wiki/index.md first — it is the navigation aid. Identify candidate pages.
  2. Read the candidate pages end to end with wiki_read_page, always passing the operation issue's wikiId and spaceSlug. Follow [[wiki-links]] to neighbouring pages when the question spans entities or concepts.
  3. Inspect raw sources when a wiki page's claim feels thin. The wiki points to raw/ precisely so you can verify before answering. Use wiki_read_source.
  4. Answer the question in the operation issue thread. Structure:
    • Direct answer first, in 1–4 sentences.
    • Then the supporting facts as bullet points, each with an inline citation: (see [[wiki/concepts/managed-resources]]) or (see raw/<filename>).
    • If you needed to read a raw source the wiki did not summarise, name that as a gap.
  5. Decide whether the answer is durable. If the question forced you to do real synthesis (a comparison, a tradeoff, a definition of something that isn't already a page), offer to file it under wiki/synthesis/<slug>.md. Do not write the synthesis page silently — it is opt-in. If the user accepts, write the page, link it from wiki/index.md, and append a query | filed synthesis log entry.
  6. When the wiki cannot answer, say so plainly. Suggest a source the user should ingest, a Paperclip project that would help if distilled, or a web lookup. Never bluff.

Voice

  • Lead with the answer.
  • Cite as you go, not in a footnote block at the end.
  • Use the wiki's terse, factual voice. The query response is itself a candidate for filing into wiki/synthesis/.

Verification

Before closing the operation issue:

  • Every claim in the answer cites a wiki page or raw source.
  • If the wiki was insufficient, that is stated directly with a concrete next step (ingest source X, distill project Y, web search Z).
  • If you wrote a synthesis page, wiki/index.md lists it and wiki/log.md has a query | filed synthesis entry.
  • No file under raw/ was modified.

Tools

wiki_search, wiki_read_page, wiki_list_sources, wiki_read_source, wiki_write_page (only when filing synthesis). Always include the operation issue's wikiId and spaceSlug.

Frequently asked questions

What does the Wiki Query AI skill do?

Use when an LLM Wiki operation issue asks a question. Answer from wiki pages and raw sources with citations, name gaps plainly, and offer to file durable synthesis when the answer should compound.

Why use Wiki Query on TypingMind?

Because you install it once and use it with any model. Wiki Query is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Wiki Query in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/paperclipai/paperclip/tree/master/packages/plugins/plugin-llm-wiki/skills/wiki-query. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Wiki Query?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Wiki Query?

As many as you like. As long as a model supports skills, you can use Wiki Query with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Wiki Query AI skill free?

Yes. It is published on GitHub by paperclipai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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