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Prd Template

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yezannnnn
prd-template

Product Requirements Document creation following proven PM template structure. Use when the user asks to create, write, draft, or help with a PRD, product requirements document, product spec, feature specification, or product documentation for a new feature or product.

Overview

Publisheryezannnnn
RepositoryagentGroup
Skill nameprd-template
Stars
149
Forks
49
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 yezannnnn on GitHub. Read the source before you install it.

Installation

Install the Prd Template 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/yezannnnn/agentGroup.git /tmp/agentGroup
mkdir -p .claude/skills
cp -r /tmp/agentGroup/max/skills/pm-claude-skills/skills/prd-template .claude/skills/prd-template
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prd Template 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 Template 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 Template 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 Template Skill

This skill helps create professional Product Requirements Documents following industry best practices.

Template Structure

Every PRD should include these sections in order:

1. Overview

  • Problem Statement: What problem are we solving? (2-3 sentences)
  • Proposed Solution: High-level description of what we're building (2-3 sentences)
  • Success Metrics: How we'll measure success (3-5 key metrics)

2. Context & Background

  • Why Now: Why is this the right time?
  • Strategic Alignment: How does this align with company objectives?
  • User Research Summary: Key insights from research (if applicable)

3. User Stories & Use Cases

Format: "As a [user type], I want to [action] so that [benefit]"

  • Include 3-7 primary user stories
  • Add acceptance criteria for each

4. Requirements

Functional Requirements:

  • Must-have features (P0)
  • Should-have features (P1)
  • Nice-to-have features (P2)

Non-Functional Requirements:

  • Performance expectations
  • Security considerations
  • Accessibility requirements

5. Design & User Experience

  • Link to design mocks or wireframes
  • Key user flows
  • Edge cases and error states

6. Technical Considerations

  • Architecture implications
  • Dependencies on other systems
  • Technical risks and mitigations

7. Implementation Plan

  • Phase 1 (MVP): What goes in first version
  • Phase 2: What comes next
  • Phase 3: Future enhancements

8. Open Questions

  • Decisions that still need to be made
  • Stakeholders to consult
  • Research needed

9. Appendix

  • Research links
  • Related documents
  • Competitive analysis

Writing Guidelines

Tone: Clear, concise, actionable Audience: Engineers, designers, stakeholders Length: Aim for 3-6 pages for features, 8-12 for products

Best Practices:

  • Use concrete examples over abstractions
  • Include "why" not just "what"
  • Make requirements testable
  • Link to supporting materials
  • Update as decisions are made

What Makes a Good PRD

Do:

  • Write from the user's perspective
  • Include specific success metrics
  • Address edge cases
  • Link to research and data
  • Make trade-offs explicit

Don't:

  • Write implementation details (that's tech spec)
  • Assume everyone has context
  • Leave requirements ambiguous
  • Skip the "why"
  • Forget about accessibility

Example PRD Opening

# PRD: Multi-Channel Customer Support Dashboard

## Overview

**Problem Statement**: Support teams are currently managing customer inquiries across email, chat, and social media using three separate tools, leading to delayed responses, duplicated work, and inconsistent customer experiences. On average, support agents waste 2.3 hours per day switching between tools and manually tracking conversation history.

**Proposed Solution**: Build a unified dashboard that aggregates customer inquiries from all channels into a single interface, maintains conversation history across channels, and provides intelligent routing based on agent expertise and availability.

**Success Metrics**:
- Reduce average response time from 4 hours to 1 hour
- Decrease tool-switching time by 80% (from 2.3 to <0.5 hours)
- Improve customer satisfaction score from 3.8 to 4.5 (out of 5)
- Increase support agent productivity by 35%

## Context & Background

**Why Now**: Customer satisfaction has declined 15% over the past 6 months, primarily due to slow response times. Our top competitor launched a unified support dashboard last quarter, and we're hearing about it in sales calls. Support team turnover is at 45% annually, with "tool complexity" cited as a top frustration.

**Strategic Alignment**: This aligns with our Q1 company objective to "Improve customer retention by 10%" and our support team's OKR to "Reduce average handle time by 25%."

**User Research Summary**: We conducted interviews with 12 support agents and observed 20 hours of support sessions. Key findings:
- Agents spend 35% of their time finding context from previous interactions
- 65% of escalations are due to lack of conversation history
- Agents rated tool-switching as their #1 daily frustration (9.2/10 pain)
- Current NPS for support experience is -12

## User Stories & Use Cases

**US1: Unified Inbox**
As a support agent, I want to see all customer inquiries in one place so that I don't miss urgent requests and can prioritize effectively.

Acceptance Criteria:
- Inbox shows inquiries from email, chat, and social media
- Inquiries are sorted by priority (urgent, high, normal, low)
- Agent can filter by channel, customer, or status
- Real-time updates when new inquiries arrive

**US2: Cross-Channel Context**
As a support agent, I want to see the full conversation history regardless of channel so that I can provide consistent, informed responses without asking customers to repeat themselves.

Acceptance Criteria:
- Timeline view shows all interactions chronologically
- Each interaction displays channel, timestamp, and content
- Customer profile shows demographics and account information
- Previous issues and resolutions are accessible

[Continue with 5-7 total user stories...]

Frequently asked questions

What does the Prd Template AI skill do?

Product Requirements Document creation following proven PM template structure. Use when the user asks to create, write, draft, or help with a PRD, product requirements document, product spec, feature specification, or product documentation for a new feature or product.

Why use Prd Template on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yezannnnn/agentGroup/tree/master/max/skills/pm-claude-skills/skills/prd-template. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Prd Template?

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 Template?

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

Is the Prd Template AI skill free?

Yes. It is published on GitHub by yezannnnn 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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