design-prd
Skill9 starsChanged 42 days agoMITView on GitHub
Generate Product Requirements Documents through structured conversation for any project. Use when starting a new feature, documenting requirements, creating specs before implementation, or needing clarity on scope and success criteria.
1 other project uses a version of this, 1 of them edited.
Adopted by
Most recently taken up by
- kensaurus/skillsedited, first seen Oct 1, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 1
- kensaurus/skills★ 965% same
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository165 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .cursor/rules/approved-plan-execution.mdcCursor rule
- .cursor/rules/skill-workflows.mdcCursor rule
- .cursor/rules/verification-before-completion.mdcCursor rule
- llms.txtllms.txt
- audit-accessibilitySkill
- audit-agent-speedSkill
- audit-analyticsSkill
- audit-auth-flowsSkill
- audit-backend-architectureSkill
- audit-bundle-sizeSkill
- audit-cicdSkill
- audit-codemod-safetySkill
- audit-code-qualitySkill
- audit-code-reviewSkill
- audit-db-schemaSkill
- audit-doctrineSkill
- audit-env-paritySkill
- audit-fe-apiSkill
- audit-gate-logicSkill
- audit-i18nSkill
- audit-infra-costSkill
- audit-langfuse-llmSkill
- audit-llm-securitySkill
- audit-monetization-iapSkill
- audit-payment-systemSkill
- audit-performanceSkill
- audit-realworldSkill
- audit-registry-listingSkill
- audit-resilienceSkill
- audit-responsiveSkill
- audit-securitySkill
- audit-skill-conflictsSkill
- audit-ui-statesSkill
- audit-uiux-design-systemSkill
- audit-ux-journeysSkill
- audit-uxSkill
- backend-db-performanceSkill
- backend-error-handlingSkill
- backend-observabilitySkill
- backend-patternsSkill
- backend-realtimeSkill
- burndown-fullSkill
- complete-everythingSkill
- data-pipelineSkill
- data-visualizationSkill
- debug-errorSkill
- debug-fe-be-integrationSkill
- debug-sentry-monitorSkill
- deploy-npmSkill
- deploy-verifySkill
- design-apiSkill
- design-canvasSkill
- design-emailSkill
- design-frontendSkill
- design-generative-artSkill
- design-mobile-firstSkill
- design-motionSkill
- design-systemSkill
- design-themeSkill
- The first 60 shown.
The file
Show its rules and text
We split this skill into the rules it gives an agent
14 rules. About 0 are common, 13 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈13
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 16
Create detailed, actionable Product Requirements Documents through structured conversation, informed by codebase analysis and competitive …
- Distinctive: line 44
Before writing any PRD, understand the project from its source code.
- Very specific: line 48
Read package.json (or equivalent) to extract:
- Distinctive: line 66
Read feature READMEs if they exist:
- Distinctive: line 107
When the user describes a feature, research how others have solved it:
- Distinctive: line 133
Check if the framework supports what the feature needs:
- Distinctive: line 153
If the feature involves data, check the existing schema:
- Distinctive: line 176
Do RLS policies need updating?
- Distinctive: line 182
When the user describes a feature, sort what is clear from what is unclear before writing anything:
- Distinctive: line 194
If similar functionality already exists, the PRD should extend it rather than duplicate.
- Distinctive: line 246
Use hyphens for spaces
- Distinctive: line 258
Every requirement is testable ("fast" is vague.
- Distinctive: line 259
Use tables for structured comparisons
- Distinctive: line 272
Not checking existing codebase (leads to duplicate features)
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Generate PRD Skill
Degree of freedom: MIXED. Clarifying questions, scope, and requirements
[HIGH freedom]; stack/feature/schema detection [LOW freedom — run exactly].
Create detailed, actionable Product Requirements Documents through structured conversation, informed by codebase analysis and competitive research.
How to reason
- Discover — stack, features, schema, existing PRDs
- Clarify — only what is unclear, numbered with lettered options
- Scope — P0/P1/P2 plus explicit non-goals
- Specify — testable requirements, not implementation
Worked example
Discover: Next.js + Supabase;
notificationstable missing; noprd-*.md. Clarify: in-app vs email vs push? (user: 1A in-app only). MVP vs polish? (2A MVP). Scope: P0 in-app bell + read state; non-goal: email/push (design-email/mobile-capacitor-platform). Specify: FR-1 "unread count on the header within 2s of insert" — not "feel realtime".
Self-critique before reporting
- Context recorded — stack, features, schema, and existing PRDs were listed first
- Questions minimal — only what was unclear, lettered; coding did not start first
- Testable FRs — no "should be fast" without a number
- Right owner — ready to implement →
workflow-build-feature; UI from scratch →design-frontend; RLS matrix →plan-rls-audit
Step 0: Auto-Detect Project Context [LOW freedom — run exactly]
Before writing any PRD, understand the project from its source code.
0a. Detect Tech Stack
Read package.json (or equivalent) to extract:
- Framework: Next.js, Remix, SvelteKit, Nuxt, Django, Rails, etc.
- UI library: React, Vue, Svelte, Angular
- Database: Supabase, Prisma, Drizzle, raw SQL
- Auth: Supabase Auth, NextAuth, Clerk, Auth0
- State management: TanStack Query, Zustand, Redux, Pinia
- CSS: Tailwind, CSS Modules, Styled Components
0b. Discover Existing Features
Glob: **/app/**/page.tsx → Next.js routes (features)
Glob: **/features/*/ → Feature directories
Glob: **/src/routes/**/*.tsx → Route-based features
Grep: pattern "export default" glob "**/page.tsx" output_mode "files_with_matches"Read feature READMEs if they exist:
Glob: **/*README*.md → Feature docs
Glob: **/docs/*.md → Documentation0c. Discover Data Model
Glob: **/supabase/migrations/*.sql → SQL migrations
Glob: **/prisma/schema.prisma → Prisma schema
Glob: **/drizzle/schema.ts → Drizzle schema
Glob: **/types/*.ts → TypeScript type definitions0d. Check for Existing PRDs
Glob: **/tasks/prd-*.md → Existing PRDs
Glob: **/docs/prd-*.md → Existing PRDs (alt location)
Glob: **/specs/*.md → Spec documents0e. Record Context
PROJECT CONTEXT:
- Framework: [name + version]
- Database: [type + ORM]
- Existing features: [list of routes/feature dirs]
- Existing PRDs: [list or none]
- Data entities: [list from schema]
- Auth system: [provider]Step 1: Research Before Writing [HIGH freedom]
1a. Competitive Research (Firecrawl)
When the user describes a feature, research how others have solved it:
firecrawl:firecrawl_search
{
"query": "<FEATURE_TYPE> UX patterns best practices [current year]",
"limit": 5,
"sources": [{ "type": "web" }]
}Feature-type search queries (CRUD, dashboard, onboarding, e-commerce, social, CMS, search, settings): references/research-and-questions.md §Feature-type search queries.
Scrape the most relevant result for detailed patterns. Competitor rows in section 7 come from fetched pages, not memory — recognizing a product name is not knowing its current feature set; search the name as written:
firecrawl:firecrawl_scrape
{
"url": "<BEST_RESULT_URL>",
"formats": ["markdown"],
"onlyMainContent": true
}1b. Technical Feasibility (Context7)
Check if the framework supports what the feature needs:
context7:resolve-library-id
{
"libraryName": "<FRAMEWORK>",
"query": "<FEATURE_CAPABILITY> support"
}context7:query-docs
{
"libraryId": "<RESOLVED_ID>",
"query": "<FEATURE_CAPABILITY> implementation guide"
}1c. Data Model Feasibility (Supabase MCP)
If the feature involves data, check the existing schema:
supabase:list_tables
{
"schemas": ["public"],
"verbose": true
}Or for specific tables:
supabase:execute_sql
{
"query": "SELECT column_name, data_type, is_nullable FROM information_schema.columns WHERE table_name = '<RELEVANT_TABLE>' ORDER BY ordinal_position"
}Determine:
- Can existing tables support this feature?
- What new tables/columns are needed?
- What relationships need to be added?
- Do RLS policies need updating?
Step 2: Understand the Request [HIGH freedom]
When the user describes a feature, sort what is clear from what is unclear before writing anything:
- Clear: problem statement, target user, basic functionality
- Unclear: scope boundaries, success metrics, edge cases, technical constraints
Check for Similar Functionality
SemanticSearch: "How does the app currently handle <FEATURE_AREA>?" target: []
Grep: pattern "<FEATURE_KEYWORDS>" glob "*.{ts,tsx,js,jsx}"If similar functionality already exists, the PRD should extend it rather than duplicate.
Step 3: Ask Clarifying Questions [HIGH freedom]
Rules
- Ask only what is truly unclear — usually a handful; if nothing is, say so and proceed
- Number all questions (1, 2, 3...)
- Provide lettered options (A, B, C, D) for easy response
- Make responding easy — user can reply "1A, 2C, 3B"
Question Categories
| Category | Ask When... |
| Problem / Goal | The "why" is unclear |
| Core Functionality | The "what" is vague |
| Scope Boundaries | Request is broad |
| Target User | Multiple user types possible |
| Success Criteria | No clear definition of "done" |
Example Format
Numbered questions, lettered A–D options, closing with Reply with selections (e.g., "1B, 2A, 3B"): references/research-and-questions.md §Clarifying questions.
Step 4: Generate PRD [HIGH freedom]
Template
Ten sections, in order: Overview (problem, proposed solution) → Goals table with success metrics → User Stories (primary + edge case) → Functional Requirements as P0/P1/P2 checkboxes → Non-Goals → Technical Feasibility (existing vs new infrastructure, complexity table) → Competitive Analysis table from the Firecrawl research → UI/UX Considerations (screens, borrowed patterns, accessibility) → Data Model (tables used, SQL for new tables, RLS policies) → Open Questions.
Full template: references/prd-template.md.
Step 5: Iterate [HIGH freedom]
Present the PRD, take the user's edits, resolve the open questions, and confirm it is ready to save before writing the file.
Step 6: Save [LOW freedom — run exactly]
Location: tasks/prd-[feature-name].md
Naming:
- All lowercase
- Use hyphens for spaces
- Examples:
prd-dark-mode.md,prd-export-csv.md,prd-user-onboarding.md
Writing Guidelines
Target audience: a junior developer should understand this.
- Clear, simple language
- Define acronyms on first use
- Be explicit — no implied knowledge
- Every requirement is testable ("fast" is vague; "loads in under 200ms" is testable)
- Use tables for structured comparisons
- Include "Not doing" section to prevent scope creep
Anti-Patterns
- Starting to code before asking questions
- Asking questions the repo or the request already answers
- Writing implementation details (PRD = WHAT/WHY, not HOW)
- Vague requirements ("should be fast" -> "response time under 200ms")
- Skipping competitive research (leads to reinventing the wheel)
- Skipping technical feasibility (leads to impossible requirements)
- Not checking existing codebase (leads to duplicate features)
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

