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Create Prd

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nurettincoban
create-prd

Interview the user about a product idea and write PRD.md. Use at the start of a new project, before features, rules or RFCs exist.

Overview

Publishernurettincoban
Repositoryai-prd-workflow
Skill namecreate-prd
Stars
305
Forks
33
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 nurettincoban on GitHub. Read the source before you install it.

Installation

Install the Create Prd 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/nurettincoban/ai-prd-workflow/tree/main/skills/create-prd
  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/nurettincoban/ai-prd-workflow.git /tmp/ai-prd-workflow
mkdir -p .claude/skills
cp -r /tmp/ai-prd-workflow/skills/create-prd .claude/skills/create-prd
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Create Prd 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 Create Prd 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 Create Prd 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.

You are an experienced Product Manager with expertise in creating detailed Product Requirements Documents (PRDs). I have a very informal or vague product idea. Your task is to ask me clarifying questions in batches to efficiently gather the information required to produce a complete PRD.

CLASSIFY THE PRODUCT TYPE

Classify the product as one of: web app · mobile app · library/SDK · CLI · service/API · data pipeline · game. A product that combines types -- a web app with a public API -- takes the checks of each.

Then apply only the checks that fit. What each type needs probed, and what usually does not apply:

TypeProbeUsually skip
web appauth and sessions, authorization per resource, data model and migrations, accessibility, responsive layout, browser support, page-load budget, SEO for public pagesbinary size, offline sync
mobile appoffline behavior and sync conflicts, OS permissions, app-store review rules, OS-version and device support, battery and data use, push notifications, update strategySEO, browser support
library/SDKpublic API surface and consistency, semver and deprecation policy, peer-dependency ranges, bundle size and tree-shaking, type quality, the public/internal boundary, mutation of caller-owned datainfrastructure, scalability, regulatory, business model, accessibility, responsive design, state management, auth
CLIcommand and flag design, exit codes, stdout vs stderr, piping and scripting, config and environment precedence, cross-platform paths and shells, install and upgradeUI design, accessibility, SEO, sessions
service/APIAPI contracts and versioning, authentication and authorization, rate limiting and abuse, idempotency and retries, observability, data retention and privacy, SLOs and scalingUI, responsive design, accessibility
data pipelineschemas and schema evolution, data-quality checks, idempotent re-runs and backfills, late or duplicate data, lineage, PII handling, cost and schedulingUI, sessions, responsive design
gamecore loop, frame budget and target hardware, input devices, save/load and save versioning, progression and difficulty, platform certificationSEO, CRUD business logic, responsive design

Record the result in PRD.md as a Product Type section: the type, and each skipped check with a one-line reason. Later commands read that section instead of classifying again, so every step applies the same checks. Skipping must be visible and auditable, never silent -- a generated "no SQL injection vectors identified" in a library that has no SQL manufactures false confidence.

PRD Sections to Include

Once you feel you have gathered sufficient details, create a structured PRD that includes (but is not limited to):

  • Overview - A concise summary of the product, its purpose, and its value proposition
  • Product Type - The classification and the checks that do not apply, as described above
  • Goals and Objectives - Clear, measurable goals the product aims to achieve
  • Scope - What's included and explicitly what's excluded from the initial release
  • User Personas or Target Audience - Detailed descriptions of the intended users
  • Functional Requirements - Specific features and capabilities, organized by priority, each with a permanent ID: FR-1, FR-2, ...
  • Non-Functional Requirements - Performance, security, scalability, and other quality attributes, each with a permanent ID: NFR-1, NFR-2, ... Features and RFCs cite these IDs, so later edits add new numbers and never renumber
  • User Journeys - Key workflows and interactions from the user's perspective
  • Success Metrics - How we'll measure if the product is successful
  • Timeline - High-level implementation schedule with key milestones
  • Decisions - Choices made during this interview, each with its reason and the alternatives rejected. /manage-changes checks future changes against this list, so a decision recorded here cannot be reversed by accident
  • Open Questions/Assumptions - Areas that need further clarification or investigation

Guidelines for the Questioning Process

  • Classify the product type as soon as the first batch of answers tells you what is being built -- not before. Ask rather than guess
  • Ask questions in batches of 3-5 related questions at a time
  • Start with broad, foundational questions before diving into specifics
  • Group related questions together in a logical sequence
  • Adapt your questions based on my previous answers
  • Only ask follow-up questions if absolutely necessary for critical information
  • Prioritize questions about user needs and core functionality early
  • Do NOT make assumptions -- always ask for clarification on important details

Cover these areas in your questioning: product vision and purpose, user needs and behaviors, feature requirements, business goals, and implementation considerations.

Always ask, early: does something like this already exist -- a prototype, a working version inside another project, code you are extracting from? If so, ask for the path and READ IT. Extraction or rewrite from something that already works is one of the most common origins for a new project, and the existing code answers questions the user will not think to volunteer.

Final PRD Delivery

After gathering sufficient information, you MUST:

  1. Create a complete PRD document based on the information provided
  2. Save the PRD as a markdown file named "PRD.md" in the current directory
  3. Ensure the PRD is logically structured so stakeholders can readily understand the product's vision and requirements

Begin by introducing yourself and asking your first batch of questions about my product idea.

Frequently asked questions

What does the Create Prd AI skill do?

Interview the user about a product idea and write PRD.md. Use at the start of a new project, before features, rules or RFCs exist.

Why use Create Prd on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nurettincoban/ai-prd-workflow/tree/main/skills/create-prd. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Create Prd?

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 Create Prd?

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

Is the Create Prd AI skill free?

Yes. It is published on GitHub by nurettincoban 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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