Automatically transforms vague requirements into actionable PRDs through systematic clarification with a 100-point scoring system.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionrequirements-clarityExecute the skills CLI command in your project's root directory to begin installation:
Fetches requirements-clarity from davila7/claude-code-templates and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate requirements-clarity. Access via /requirements-clarity in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Automatically transforms vague requirements into actionable PRDs through systematic clarification with a 100-point scoring system.
When invoked, detect vague requirements:
Vague Feature Requests
Missing Technical Context
Incomplete Specifications
Ambiguous Scope
Do NOT activate when:
Systematic Questioning
Quality-Driven Iteration
Actionable Output
Input: User's requirement description
Tasks:
1.0 unless user specifies otherwise)./docs/prds/ exists for PRD outputAssessment Rubric:
Functional Clarity: /30 points
- Clear inputs/outputs: 10 pts
- User interaction defined: 10 pts
- Success criteria stated: 10 pts
Technical Specificity: /25 points
- Technology stack mentioned: 8 pts
- Integration points identified: 8 pts
- Constraints specified: 9 pts
Implementation Completeness: /25 points
- Edge cases considered: 8 pts
- Error handling mentioned: 9 pts
- Data validation specified: 8 pts
Business Context: /20 points
- Problem statement clear: 7 pts
- Target users identified: 7 pts
- Success metrics defined: 6 pts
Initial Response Format:
I understand your requirement. Let me help you refine this specification.
**Current Clarity Score**: X/100
**Clear Aspects**:
- [List what's clear]
**Needs Clarification**:
- [List gaps]
Let me systematically clarify these points...
Identify missing information across four dimensions:
1. Functional Scope
2. User Interaction
3. Technical Constraints
4. Business Value
Question Strategy:
Question Format:
I need to clarify the following points to complete the requirements document:
1. **[Category]**: [Specific question]?
- For example: [Example if helpful]
2. **[Category]**: [Specific question]?
3. **[Category]**: [Specific question]?
Please provide your answers, and I'll continue refining the PRD.
After Each User Response:
Score Update Format:
Thank you for the additional information!
**Clarity Score Update**: X/100 → Y/100
**New Clarified Content**:
- [Summarize new information]
**Remaining Points to Clarify**:
- [List remaining gaps if score < 90]
[If score < 90: Continue with next round of questions]
[If score ≥ 90: "Perfect! I will now generate the complete PRD document..."]
Once clarity score ≥ 90, generate comprehensive PRD.
Output File:
./docs/prds/{feature_name}-v{version}-prd.mdUse the Write tool to create or update this file. Derive {version} from the document version recorded in the PRD (default 1.0).
# {Feature Name} - Product Requirements Document (PRD)
## Requirements Description
### Background
- **Business Problem**: [Describe the business problem to solve]
- **Target Users**: [Target user groups]
- **Value Proposition**: [Value this feature brings]
### Feature Overview
- **Core Features**: [List of main features]
- **Feature Boundaries**: [What is and isn't included]
- **User Scenarios**: [Typical usage scenarios]
### Detailed Requirements
- **Input/Output**: [Specific input/output specifications]
- **User Interaction**: [User operation flow]
- **Data Requirements**: [Data structures and validation rules]
- **Edge Cases**: [Edge case handling]
## Design Decisions
### Technical Approach
- **Architecture Choice**: [Technical architecture decisions and rationale]
- **Key Components**: [List of main technical components]
- **Data Storage**: [Data models and storage solutions]
- **Interface Design**: [API/interface specifications]
### Constraints
- **Performance Requirements**: [Response time, throughput, etc.]
- **Compatibility**: [System compatibility requirements]
- **Security**: [Security considerations]
- **Scalability**: [Future expansion considerations]
### Risk Assessment
- **Technical Risks**: [Potential technical risks and mitigation plans]
- **Dependency Risks**: [External dependencies and alternatives]
- **Schedule Risks**: [Timeline risks and response strategies]
## Acceptance Criteria
### Functional Acceptance
- [ ] Feature 1: [Specific acceptance conditions]
- [ ] Feature 2: [Specific acceptance conditions]
- [ ] Feature 3: [Specific acceptance conditions]
### Quality Standards
- [ ] Code Quality: [Code standards and review requirements]
- [ ] Test Coverage: [Testing requirements and coverage]
- [ ] Performance Metrics: [Performance test pass criteria]
- [ ] Security Review: [Security review requirements]
### User Acceptance
- [ ] User Experience: [UX acceptance criteria]
- [ ] Documentation: [Documentation delivery requirements]
- [ ] Training Materials: [If needed, training material requirements]
## Execution Phases
### Phase 1: Preparation
**Goal**: Environment preparation and technical validation
- [ ] Task 1: [Specific task description]
- [ ] Task 2: [Specific task description]
- **Deliverables**: [Phase deliverables]
- **Time**: [Estimated time]
### Phase 2: Core Development
**Goal**: Implement core functionality
- [ ] Task 1: [Specific task description]
- [ ] Task 2: [Specific task description]
- **Deliverables**: [Phase deliverables]
- **Time**: [Estimated time]
### Phase 3: Integration & Testing
**Goal**: Integration and quality assurance
- [ ] Task 1: [Specific task description]
- [ ] Task 2: [Specific task description]
- **Deliverables**: [Phase deliverables]
- **Time**: [Estimated time]
### Phase 4: Deployment
**Goal**: Release and monitoring
- [ ] Task 1: [Specific task description]
- [ ] Task 2: [Specific task description]
- **Deliverables**: [Phase deliverables]
- **Time**: [Estimated time]
---
Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Steps
- 1Install skill using provided installation command
- 2Test with simple use case relevant to your work
- 3Evaluate output quality and relevance
- 4Iterate on prompts to improve results
- 5Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
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Frontendsame categoryReviews
4.6★★★★★51 reviews- SSakura Perez★★★★★Dec 28, 2024
We added requirements-clarity from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- EEmma Tandon★★★★★Dec 24, 2024
Useful defaults in requirements-clarity — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- GGanesh Mohane★★★★★Dec 16, 2024
Keeps context tight: requirements-clarity is the kind of skill you can hand to a new teammate without a long onboarding doc.
- DDev Smith★★★★★Dec 12, 2024
Registry listing for requirements-clarity matched our evaluation — installs cleanly and behaves as described in the markdown.
- EEmma Menon★★★★★Dec 4, 2024
Keeps context tight: requirements-clarity is the kind of skill you can hand to a new teammate without a long onboarding doc.
- OOlivia Sharma★★★★★Nov 23, 2024
requirements-clarity has been reliable in day-to-day use. Documentation quality is above average for community skills.
- MMei Gill★★★★★Nov 19, 2024
requirements-clarity reduced setup friction for our internal harness; good balance of opinion and flexibility.
- SSakshi Patil★★★★★Nov 7, 2024
requirements-clarity has been reliable in day-to-day use. Documentation quality is above average for community skills.
- IIsabella Zhang★★★★★Nov 3, 2024
I recommend requirements-clarity for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- MMei Ghosh★★★★★Nov 3, 2024
requirements-clarity fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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