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Duck

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LeeJuOh
duck

Rubber duck tutor — auto-detects which review mode to run. Use when the user says "duck", "tutor", "quiz me", "do I understand this", or mentions rubber-stamping or learning while coding. For a specific phase use /duck-prebuild, /duck-verify, /duck-review, or /duck-orient.

Overview

PublisherLeeJuOh
Repositoryclaude-code-zero
Skill nameduck
Stars
53
Forks
4
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 LeeJuOh on GitHub. Read the source before you install it.

Installation

Install the Duck 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/LeeJuOh/claude-code-zero/tree/main/plugins/rubber-duck-tutor/skills/duck
  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/LeeJuOh/claude-code-zero.git /tmp/claude-code-zero
mkdir -p .claude/skills
cp -r /tmp/claude-code-zero/plugins/rubber-duck-tutor/skills/duck .claude/skills/duck
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Duck 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 Duck 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 Duck 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.

Duck (auto-detect)

Auto-detects which mode fits the user's current state and routes to the matching mode skill. Read ../ducking/engine.md for shared persona, principles, and session-management rules — they apply to every mode.

Paths for engine.md's commands: <scripts> is ${CLAUDE_PLUGIN_ROOT}/skills/ducking/scripts, <data-dir> is ${CLAUDE_PLUGIN_DATA}.

Mode Map

Trigger phrase / stateMode skill
"build this for me" / stated implementation intent, no plan or code yet/duck-prebuild
Active plan in conversation (or .claude/orientation.md-adjacent design doc)/duck-prebuild
Files recently created/modified in this session/duck-verify
Uncommitted changes (git diff --stat non-empty)/duck-review
User new to the repo, returning after long break, "where should I even start"/duck-orient
None of the aboveAsk the user which phase they want

Detection Order

Check in this order — first match wins:

  1. Pre-coding intent — user just stated they want to build X but no plan/diff/code exists yet → /duck-prebuild
  2. Plan in context — a plan or design doc was produced in this session → /duck-prebuild
  3. Uncommitted changes — git diff --stat shows a real diff → /duck-review
  4. Recent in-session edits — files were created or modified earlier in this session but not yet committed → /duck-verify
  5. Orientation gap — user appears unfamiliar with the repo → /duck-orient
  6. Ambiguous — ask the user which phase they want before continuing

Behavior When the User Picks Their Own Mode

If the user named a mode (prebuild, verify, review, orient — or the older design/plan words, both alias to prebuild), suggest the matching /duck-<mode> command and stop — don't run the mode flow inline. The dedicated mode skill carries the full instructions for that flow.

If the user passed $ARGUMENTS and it matches a known mode word, hand off to /duck-<mode> (map design/plan → prebuild; otherwise use $ARGUMENTS as-is):

"🦆 Quack — you want /duck-<mode>. Call it directly instead."

Otherwise apply the detection order above.

Sticking to Auto Mode

If the user wants to keep going inside /duck instead of switching to the mode-specific command, run the matching mode's flow inline. The mode-specific SKILL.md files contain the canonical flows — read the file and follow it.

Shared Rules

All persona, opening line, "Wait for their answer", Confidence Check, Intensity Scaling, Uncertainty Check, Session Wrap-up + gap persistence, Branch-first workflow + fallback, Session Limits, Facilitation, and Gotchas live in ../ducking/engine.md. Read it before running any flow.

Frequently asked questions

What does the Duck AI skill do?

Rubber duck tutor — auto-detects which review mode to run. Use when the user says "duck", "tutor", "quiz me", "do I understand this", or mentions rubber-stamping or learning while coding. For a specific phase use /duck-prebuild, /duck-verify, /duck-review, or /duck-orient.

Why use Duck on TypingMind?

Because you install it once and use it with any model. Duck 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 Duck in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LeeJuOh/claude-code-zero/tree/main/plugins/rubber-duck-tutor/skills/duck. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Duck?

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 Duck?

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

Is the Duck AI skill free?

Yes. It is published on GitHub by LeeJuOh 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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