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Maestro Questionnaire

Community
ReinaMacCredy
maestro-questionnaire

Turn a decision the user cannot fully answer into a Markdown questionnaire for the one person who can - filled in async, or together over a meeting. Also triggers on Vietnamese phrasings such as phỏng vấn đi, phỏng vấn tôi, interview tôi.

Overview

PublisherReinaMacCredy
Repositorymaestro
Skill namemaestro-questionnaire
Stars
232
Forks
23
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 ReinaMacCredy on GitHub. Read the source before you install it.

Installation

Install the Maestro Questionnaire 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.
  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/ReinaMacCredy/maestro.git /tmp/maestro
mkdir -p .claude/skills
cp -r /tmp/maestro/src/plugins/skills/maestro-questionnaire .claude/skills/maestro-questionnaire
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Maestro Questionnaire 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 Maestro Questionnaire 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 Maestro Questionnaire 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.

maestro-questionnaire

Turn something the user cannot answer alone into a questionnaire: a Markdown document they hand to one person to fill in async, or fill out together over a meeting. The recipient holds knowledge the user lacks; the questionnaire pulls it out of them. Read-only toward code; any tier may use it.

Grill the send, not the subject. Interview the user only about the send, which they can always answer: who it goes to, and what they need back. The questions in the document then target the gap between what the recipient knows and what the user needs.

  1. Who is it going to? Ask, in one exchange, the recipient's role, expertise, and relationship to the user. This fixes the questionnaire's tone and how much context it must carry. Done when you know who the recipient is and what they know that the user does not.

  2. What do you need back? Ask, in one exchange, the specific decisions or facts the user cannot resolve alone and needs from this person. Done when you have a concrete list of what the user must walk away able to do or decide.

  3. Write the questionnaire. Draft questions aimed at the gap from steps 1 and 2, following the Document structure below. When an active bundle owns the decision, write it to .maestro/bundle/<bundle-id>/QUESTIONNAIRE-<slug>.md, record the wait as maestro work note <id> "blocked: questionnaire <slug> sent to <role>", and set the bundle's NOTES.md Next Action to the return of the answers; otherwise write questionnaire-<slug>.md in the current directory. Report the path. Done when the file exists and every item the user named in step 2 is covered by a question.

When the answers come back, they are settled forks: record each as maestro decision draft "<answer>" --rationale "<why, per <recipient>>" --work <id> then maestro decision lock <id>, and clear the Next Action. The filled questionnaire is the evidence the decision cites.

Document structure

Frame the document as a discovery questionnaire: the user lacks context, the recipient holds it. Order questions most-important-first, since async means you may only get one pass, and group them under ## headings by theme once there are more than a handful. Write it using the template below.

Purpose: why this questionnaire exists and the decision riding on it.

From: To: How your answers will be used:

Context

One paragraph orienting a recipient who was not in the user's head. Enough to answer well, not a page.

How to answer

Deadline and rough effort. Partial answers and "I don't know" are useful; flag anything you are unsure of rather than skipping it.

One ## section per theme. Under each, its questions, most-important-first. Every question is one idea, never compound, with an answer stub directly beneath, and a one-line why this matters only where the question could be misread or invite a throwaway answer.

Why this matters: it decides whether we provision for burst traffic now or defer it.

Anything else?

A closing catch-all: anything we did not ask that we should know?

Frequently asked questions

What does the Maestro Questionnaire AI skill do?

Turn a decision the user cannot fully answer into a Markdown questionnaire for the one person who can - filled in async, or together over a meeting. Also triggers on Vietnamese phrasings such as phỏng vấn đi, phỏng vấn tôi, interview tôi.

Why use Maestro Questionnaire on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ReinaMacCredy/maestro/tree/main/src/plugins/skills/maestro-questionnaire. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Maestro Questionnaire?

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 Maestro Questionnaire?

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

Is the Maestro Questionnaire AI skill free?

Yes. It is published on GitHub by ReinaMacCredy 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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