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LLM Wiki Maintainer

OrganizationPopular
paperclipai
LLM Wiki Maintainer

Use the LLM Wiki plugin tools to maintain a cited local company wiki.

Overview

Publisherpaperclipai
Repositorypaperclip
Skill nameLLM Wiki Maintainer
Stars
95.4K
Forks
16.2K
Bundled files
Instructions only
LicenseMIT
Links
  • 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 LLM Wiki Maintainer 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-maintainer
  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-maintainer .claude/skills/paperclipai-llm-wiki-maintainer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable LLM Wiki Maintainer 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 LLM Wiki Maintainer 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 LLM Wiki Maintainer 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.

LLM Wiki Maintainer

Use this skill when maintaining the company LLM Wiki, answering questions from it, ingesting durable source material, refreshing the index, or linting wiki structure.

Before changing wiki files, resolve the configured wiki root, read its AGENTS.md, inspect wiki/index.md and recent wiki/log.md entries, then use the LLM Wiki plugin tools for source reads, page writes, patch proposals, backlinks, and logging.

Keep raw sources immutable, cite wiki pages and raw paths, update wiki/index.md when page navigation changes, and append a concise wiki/log.md entry for durable updates. For Paperclip project work, keep wiki/projects/<project-slug>/standup.md current as the executive status view and use wiki/projects/<project-slug>/index.md for durable project knowledge. Write project material as concept-grouped executive synthesis, not issue-id lists or metadata dumps.

Frequently asked questions

What does the LLM Wiki Maintainer AI skill do?

Use the LLM Wiki plugin tools to maintain a cited local company wiki.

Why use LLM Wiki Maintainer on TypingMind?

Because you install it once and use it with any model. LLM Wiki Maintainer 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 LLM Wiki Maintainer 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-maintainer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use LLM Wiki Maintainer?

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 LLM Wiki Maintainer?

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

Is the LLM Wiki Maintainer 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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