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Prd Writing

Community
AsyrafHussin
prd-writing

Step-by-step workflow for writing Product Requirements Documents. Use when creating PRDs, documenting features, writing specifications, or planning new products. Triggers on "write PRD", "create PRD", "document requirements", "feature spec", or "product requirements".

Overview

PublisherAsyrafHussin
Repositoryagent-skills
Skill nameprd-writing
Stars
78
Forks
10
Bundled files
29
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.

  • 29 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Prd Writing 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/AsyrafHussin/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/skills/prd-writing .claude/skills/prd-writing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prd Writing 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 Prd Writing 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 Prd Writing 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.

PRD Writing

Step-by-step workflow for writing clear, actionable Product Requirements Documents. Follow the 6-step process below, using the 25 rules across 7 categories as supporting knowledge.

Metadata

  • Version: 1.0.0
  • Rule Count: 25 rules across 7 categories
  • License: MIT

Workflow

Follow these steps in order. Skip a step only if the user has already provided that information. Do NOT start drafting before completing discovery.

Step 1: Assess Project State

Determine what you're working with:

  • Existing project — code exists → explore the codebase first (models, routes, controllers, auth, patterns). See disc-codebase-exploration.
  • Empty/greenfield project — no code yet → ask the user what they want to build first. Brainstorm together until the product idea and core features are clear, then ask about planned stack, architecture decisions, and constraints.

Step 2: Ask Clarifying Questions

Ask 3-5 targeted questions to fill knowledge gaps. Use lettered options (A/B/C) when there are clear choices, and open-ended questions when you need free-text answers. Focus on:

  1. Problem — What problem are we solving? Why now?
  2. Users — Who are the target users?
  3. Scope — What should it NOT do?
  4. Success — How do we know it's done?
  5. Constraints — Timeline, budget, team size?

Mark unknowns as TBD, not assumptions. See disc-clarifying-questions.

Step 3: Draft the PRD

Use the template from struct-prd-template and fill in all 12 sections:

  1. Executive Summary — 1 paragraph: problem, solution, impact
  2. Problem Statement — what, who, evidence, why now
  3. Goals & Success Metrics — 3-5 measurable KPIs
  4. User Personas — primary and secondary with roles/goals/pain points
  5. User Stories & Acceptance Criteria — "As a / I want / So that" with checkboxes
  6. Functional Requirements — numbered FR-1, FR-2, etc.
  7. Non-Functional Requirements — performance, security, accessibility with specific numbers
  8. Technical Specifications — data model, auth, routes, integrations
  9. Out of Scope — what we're NOT building and why
  10. Non-Goals — what we're NOT optimizing for
  11. Dependencies & Risks — blockers with owners and mitigations
  12. Open Questions — unresolved items with owners and due dates

Key rules to follow while drafting:

  • Start with the problem, not the solution (disc-problem-first)
  • Replace vague language with numbers (metric-no-vague-language)
  • Every requirement must be testable (quality-acceptance-criteria)
  • Use Given/When/Then for complex acceptance criteria

Step 4: Present for Review

Show the draft to the user. Ask specifically:

  • Does the problem statement match your understanding?
  • Are user stories missing any workflows?
  • Are the scope boundaries correct?
  • Any open questions I should resolve?

Step 5: Revise Based on Feedback

Incorporate feedback, resolve open questions, and update the PRD. Add a review history entry if the PRD will be shared with a team.

Step 6: Save the PRD

Save to docs/prd/{feature-name}.md using kebab-case naming. Include frontmatter:

markdown
---
title: Feature Name
status: draft
author: Author Name
created: YYYY-MM-DD
updated: YYYY-MM-DD
---

Rules Reference

The 25 rules below provide detailed guidance for each step. Read them when you need deeper context.

1. Discovery (CRITICAL)

  • disc-problem-first - Start with the problem, not the solution
  • disc-clarifying-questions - Ask clarifying questions before writing
  • disc-codebase-exploration - Explore the codebase before drafting
  • disc-stakeholder-alignment - Align with stakeholders on goals and constraints

2. Structure (CRITICAL)

  • struct-standard-sections - Use standardized PRD sections
  • struct-executive-summary - Write a concise executive summary
  • struct-prd-template - Provide a ready-to-use PRD template
  • struct-output-location - Save PRDs to a consistent file location
  • struct-single-source-of-truth - PRD is the definitive reference for a feature

3. Requirements (HIGH)

  • req-user-personas - Define target user personas
  • req-user-stories - Write user stories with acceptance criteria
  • req-functional - Define specific functional requirements
  • req-non-functional - Define non-functional requirements

4. Scope (HIGH)

  • scope-out-of-scope - Explicitly define what is out of scope
  • scope-non-goals - List non-goals to protect timeline
  • scope-dependencies - Identify dependencies and blockers

5. Metrics (HIGH)

  • metric-measurable-success - Define measurable success criteria
  • metric-no-vague-language - Replace vague terms with quantifiable benchmarks
  • metric-kpis - Define 3-5 key performance indicators

6. Technical (MEDIUM)

  • tech-data-model - Document the data model and relationships
  • tech-auth-model - Define authentication and authorization
  • tech-api-routes - Document API and route structure
  • tech-integration-points - Identify third-party integrations

7. Quality (MEDIUM)

  • quality-acceptance-criteria - Write testable acceptance criteria
  • quality-iterative-review - Iterate with feedback before finalizing

References

Full Compiled Document

For the complete guide with all rules expanded: AGENTS.md

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Prd Writing AI skill do?

Step-by-step workflow for writing Product Requirements Documents. Use when creating PRDs, documenting features, writing specifications, or planning new products. Triggers on "write PRD", "create PRD", "document requirements", "feature spec", or "product requirements".

Why use Prd Writing on TypingMind?

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

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

Which AI models can use Prd Writing?

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 Prd Writing?

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

Is the Prd Writing AI skill free?

Yes. It is published on GitHub by AsyrafHussin 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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