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Prd Writing

Community
assimovt
prd-writing

Write structured, opinionated PRDs that engineers actually read. Use when asked to write a PRD, product spec, feature requirements, or product requirements document. Creates concise, evidence-backed specs with clear scope boundaries and measurable success criteria.

Overview

Publisherassimovt
Repositoryproductskills
Skill nameprd-writing
Stars
71
Forks
6
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 assimovt 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.
    https://github.com/assimovt/productskills/tree/main/skills/prd-writing
  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/assimovt/productskills.git /tmp/productskills
mkdir -p .claude/skills
cp -r /tmp/productskills/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.

Write PRDs that are evidence-first, concise, and scannable. A PRD is a thinking tool — if it's longer than 1200 words, the author hasn't thought hard enough. Brief specs are more likely to be read, more likely to be followed, and more likely to ship on time.

Structure

Follow this structure. Every section is mandatory unless marked optional.

1. Problem

Lead with customer evidence. Quotes, data, support tickets, observed behavior. If you have no evidence, say so explicitly — that's an opinion-driven PRD and should be flagged.

Example:

"3 of 5 interviewed customers abandon onboarding at the team invite step. Average time spent: 47 seconds before closing the tab."

NOT: "Users find onboarding confusing."

2. Goals

Measurable outcomes, not outputs. Each goal has a number attached.

  • "Reduce onboarding drop-off from 60% to under 30%"
  • NOT "Improve the onboarding experience"

3. Target Users

Who specifically benefits. Be narrow. "Series A startup founders doing PM work before their first PM hire" — not "product managers."

4. Requirements

Use P0/P1/P2 with clear definitions:

  • P0 — Does not ship without it. The feature is broken or useless without this.
  • P1 — Ships without it, but significantly degraded. Do in same cycle if possible.
  • P2 — Nice to have. Candidate for fast follow.

Each requirement is one sentence. If a requirement needs a paragraph to explain, it's too big — break it down.

5. Success Metrics

Numbers. Always numbers. "Reduce X from Y to Z within W weeks."

ALWAYS pair each metric with a counter-metric to prevent gaming:

  • Metric: "Increase activation rate to 70%"
  • Counter-metric: "Without decreasing 30-day retention below 45%"

6. Out of Scope

What you are deliberately NOT building and why. This section prevents scope creep and signals that you've thought about boundaries.

7. Open Questions (optional)

Unresolved decisions that need input. Each question names who should answer it and by when.

Guidelines

  • CRITICAL: 800-1200 words maximum. Longer PRDs mean the thinking isn't done.
  • NEVER start from a solution. Start from a problem with evidence.
  • NEVER include implementation details — architecture, APIs, database schemas. That's spec territory, not PRD territory.
  • ALWAYS include Out of Scope. A PRD without boundaries invites scope creep.
  • ALWAYS trace requirements to customer evidence. No evidence = opinion.
  • NEVER use weasel metrics: "improve performance," "enhance experience," "increase engagement." Put a number on it or don't include it.
  • P0 requirements should number 3-5. If you have more than 5 P0s, you haven't prioritized.

Example: Good vs Bad

Bad P0 requirement:

"The system should handle authentication in a secure and user-friendly manner, supporting multiple providers and edge cases."

Good P0 requirement:

"P0: User can sign up and log in with email + password. Google OAuth is P1."

One sentence. Clear scope. Priority forces a decision.


Built on Linear's "short specs > exhaustive docs" philosophy. Skills from productskills.

Frequently asked questions

What does the Prd Writing AI skill do?

Write structured, opinionated PRDs that engineers actually read. Use when asked to write a PRD, product spec, feature requirements, or product requirements document. Creates concise, evidence-backed specs with clear scope boundaries and measurable success criteria.

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/assimovt/productskills/tree/main/skills/prd-writing. TypingMind reads its SKILL.md 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 assimovt 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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