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Skills github awesome-copilot

prd

Use it when:
You're starting a product or feature, including an AI-powered one, and want its requirements pinned down before building.
It does:
Asks at least two questions first, on the problem, how success is measured and the constraints, then maps the user flow and non-goals.
You get:
A PRD with an executive summary, user stories with acceptance criteria, AI requirements if any, technical specs, and risks with a phased roadmap.
Insists on:
Measurable requirements, such as results within 200ms for 10k records, rather than "fast" or "easy"; a tech stack you didn't name is asked about or marked TBD.

TL;DR

A PRD (product requirements document) is the single source of truth for what a project will and won't build. This skill never writes one without discovery: the agent first asks why this is being built now, how you'll know it worked, and what budget, stack or deadline limits it. It then works out dependencies and hidden complexity, the user flow, and what's explicitly out of scope, and drafts the document in a strict schema. The executive summary states the problem, the proposed solution and three to five measurable KPIs. The user experience section lists personas, user stories in "As a [user], I want to [action] so that [benefit]" form, acceptance criteria for each, and non-goals. AI features get a section on the tools and APIs they need and how output quality will be evaluated and tested. Technical specifications cover the architecture, integration points such as APIs, databases and auth, and security and privacy. The last section plans a phased rollout from MVP to v2.0 and names technical risks such as latency, cost or failing dependencies. It presents a draft and asks for feedback on specific sections. A worked example covers an intelligent documentation search.

Summarizes the skill at 797337f.

npx skills add https://github.com/github/awesome-copilot --skill prd

skills.sh pageSource on GitHubAll skills from github/awesome-copilot

Total Downloads
24,400 on skills.sh, Nov 9, 2026
Repo stars
40,943 github/awesome-copilot
First seen
Jan 23, 2026 on skills.sh
Weekly Downloads
185
-9% over the 8 weeks to Nov 9
Weekly values
Week toInstalls
Sep 21203
Sep 28221
Oct 5240
Oct 12172
Oct 19201
Oct 26175
Nov 2175
Nov 9185
Category
category:planningcategory:software-engineering

Make the agent question you and write the plan down before it writes code.

Everything for building software: planning, coding, debugging, design, frameworks, cloud, agents and skills.
Type
type:workflow

A multi-step process the agent follows: interview, debug, run a TDD loop, review.
Effect
effect:none

Adds no side effects of its own. It shapes how the agent thinks, writes or reviews. Guidelines and routers are always effect:none, even when the task they support edits code.
Needs
needs:none

Instructions only. Works in any agent that supports skills.
Publisher
by:official

A verified publisher on skills.sh, or the company or maintainer behind the product the skill operates.
Topics
requirementsplanninginterview

SKILL.md

From github/awesome-copilot at 797337f. Checked daily, last changed Nov 6, 2026.

Frontmatter
name: prd
description: 'Generate high-quality Product Requirements Documents (PRDs) for software systems and AI-powered features. Includes executive summaries, user stories, technical specifications, and risk analysis.'
license: MIT

Product Requirements Document (PRD)

Overview

Design comprehensive, production-grade Product Requirements Documents (PRDs) that bridge the gap between business vision and technical execution. This skill works for modern software systems, ensuring that requirements are clearly defined.

When to Use

Use this skill when:

  • Starting a new product or feature development cycle
  • Translating a vague idea into a concrete technical specification
  • Defining requirements for AI-powered features
  • Stakeholders need a unified "source of truth" for project scope
  • User asks to "write a PRD", "document requirements", or "plan a feature"

Operational Workflow

Phase 1: Discovery (The Interview)

Before writing a single line of the PRD, you MUST interrogate the user to fill knowledge gaps. Do not assume context.

Ask about:

  • The Core Problem: Why are we building this now?
  • Success Metrics: How do we know it worked?
  • Constraints: Budget, tech stack, or deadline?
Phase 2: Analysis & Scoping

Synthesize the user's input. Identify dependencies and hidden complexities.

  • Map out the User Flow.
  • Define Non-Goals to protect the timeline.
Phase 3: Technical Drafting

Generate the document using the Strict PRD Schema below.

PRD Quality Standards

Requirements Quality

Use concrete, measurable criteria. Avoid "fast", "easy", or "intuitive".

# Vague (BAD)
- The search should be fast and return relevant results.
- The UI must look modern and be easy to use.

# Concrete (GOOD)
+ The search must return results within 200ms for a 10k record dataset.
+ The search algorithm must achieve >= 85% Precision@10 in benchmark evals.
+ The UI must follow the 'Vercel/Next.js' design system and achieve 100% Lighthouse Accessibility score.

Strict PRD Schema

You MUST follow this exact structure for the output:

1. Executive Summary
  • Problem Statement: 1-2 sentences on the pain point.
  • Proposed Solution: 1-2 sentences on the fix.
  • Success Criteria: 3-5 measurable KPIs.
2. User Experience & Functionality
  • User Personas: Who is this for?
  • User Stories: As a [user], I want to [action] so that [benefit].
  • Acceptance Criteria: Bulleted list of "Done" definitions for each story.
  • Non-Goals: What are we NOT building?
3. AI System Requirements (If Applicable)
  • Tool Requirements: What tools and APIs are needed?
  • Evaluation Strategy: How to measure output quality and accuracy.
4. Technical Specifications
  • Architecture Overview: Data flow and component interaction.
  • Integration Points: APIs, DBs, and Auth.
  • Security & Privacy: Data handling and compliance.
5. Risks & Roadmap
  • Phased Rollout: MVP -> v1.1 -> v2.0.
  • Technical Risks: Latency, cost, or dependency failures.

Implementation Guidelines

DO (Always)
  • Define Testing: For AI systems, specify how to test and validate output quality.
  • Iterate: Present a draft and ask for feedback on specific sections.
DON'T (Avoid)
  • Skip Discovery: Never write a PRD without asking at least 2 clarifying questions first.
  • Hallucinate Constraints: If the user didn't specify a tech stack, ask or label it as TBD.

Example: Intelligent Search System

1. Executive Summary

Problem: Users struggle to find specific documentation snippets in massive repositories. Solution: An intelligent search system that provides direct answers with source citations. Success:

  • Reduce search time by 50%.
  • Citation accuracy >= 95%.
2. User Stories
  • Story: As a developer, I want to ask natural language questions so I don't have to guess keywords.
  • AC:
    • Supports multi-turn clarification.
    • Returns code blocks with "Copy" button.
3. AI System Architecture
  • Tools Required: codesearch, grep, webfetch.
4. Evaluation
  • Benchmark: Test with 50 common developer questions.
  • Pass Rate: 90% must match expected citations.