requirements-clarity

softaworks/agent-toolkit · updated Apr 8, 2026

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$npx skills add https://github.com/softaworks/agent-toolkit --skill requirements-clarity
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summary

Automatically transforms vague requirements into actionable PRDs through systematic clarification with a 100-point scoring system.

skill.md

Requirements Clarity Skill

Description

Automatically transforms vague requirements into actionable PRDs through systematic clarification with a 100-point scoring system.

Instructions

When invoked, detect vague requirements:

  1. Vague Feature Requests

    • User says: "add login feature", "implement payment", "create dashboard"
    • Missing: How, with what technology, what constraints?
  2. Missing Technical Context

    • No technology stack mentioned
    • No integration points identified
    • No performance/security constraints
  3. Incomplete Specifications

    • No acceptance criteria
    • No success metrics
    • No edge cases considered
    • No error handling mentioned
  4. Ambiguous Scope

    • Unclear boundaries ("user management" - what exactly?)
    • No distinction between MVP and future enhancements
    • Missing "what's NOT included"

Do NOT activate when:

  • Specific file paths mentioned (e.g., "auth.go:45")
  • Code snippets included
  • Existing functions/classes referenced
  • Bug fixes with clear reproduction steps

Core Principles

  1. Systematic Questioning

    • Ask focused, specific questions
    • One category at a time (2-3 questions per round)
    • Build on previous answers
    • Avoid overwhelming users
  2. Quality-Driven Iteration

    • Continuously assess clarity score (0-100)
    • Identify gaps systematically
    • Iterate until ≥ 90 points
    • Document all clarification rounds
  3. Actionable Output

    • Generate concrete specifications
    • Include measurable acceptance criteria
    • Provide executable phases
    • Enable direct implementation

Clarification Process

Step 1: Initial Requirement Analysis

Input: User's requirement description

Tasks:

  1. Parse and understand core requirement
  2. Generate feature name (kebab-case format)
  3. Determine document version (default 1.0 unless user specifies otherwise)
  4. Ensure ./docs/prds/ exists for PRD output
  5. Perform initial clarity assessment (0-100)

Assessment 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...

Step 2: Gap Analysis

Identify missing information across four dimensions:

1. Functional Scope

  • What is the core functionality?
  • What are the boundaries?
  • What is out of scope?
  • What are edge cases?

2. User Interaction

  • How do users interact?
  • What are the inputs?
  • What are the outputs?
  • What are success/failure scenarios?

3. Technical Constraints

  • Performance requirements?
  • Compatibility requirements?
  • Security considerations?
  • Scalability needs?

4. Business Value

  • What problem does this solve?
  • Who are the target users?
  • What are success metrics?
  • What is the priority?

Step 3: Interactive Clarification

Question Strategy:

  1. Start with highest-impact gaps
  2. Ask 2-3 questions per round
  3. Build context progressively
  4. Use user's language
  5. Provide examples when helpful

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:

  1. Update clarity score
  2. Capture new information in the working PRD outline
  3. Identify remaining gaps
  4. If score < 90: Continue with next round of questions
  5. If score ≥ 90: Proceed to PRD generation

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..."]

Step 4: PRD Generation

Once clarity score ≥ 90, generate comprehensive PRD.

Output File:

  1. Final PRD: ./docs/prds/{feature_name}-v{version}-prd.md

Use the Write tool to create or update this file. Derive {version} from the document version recorded in the PRD (default 1.0).

PRD Document Structure

# {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]

---

how to use requirements-clarity

How to use requirements-clarity on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add requirements-clarity
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/softaworks/agent-toolkit --skill requirements-clarity

The skills CLI fetches requirements-clarity from GitHub repository softaworks/agent-toolkit and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/requirements-clarity

Reload or restart Cursor to activate requirements-clarity. Access the skill through slash commands (e.g., /requirements-clarity) or your agent's skill management interface.

Security & Verification Notice

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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

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

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate 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

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.538 reviews
  • Shikha Mishra· Dec 24, 2024

    Registry listing for requirements-clarity matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Ava Thompson· Dec 8, 2024

    requirements-clarity fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Zara Wang· Dec 4, 2024

    I recommend requirements-clarity for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Ava Gupta· Nov 27, 2024

    We added requirements-clarity from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Tariq Desai· Nov 23, 2024

    Useful defaults in requirements-clarity — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Yash Thakker· Nov 15, 2024

    Solid pick for teams standardizing on skills: requirements-clarity is focused, and the summary matches what you get after install.

  • Ava Okafor· Oct 18, 2024

    Keeps context tight: requirements-clarity is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Zara Sanchez· Oct 14, 2024

    Registry listing for requirements-clarity matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Dhruvi Jain· Oct 6, 2024

    I recommend requirements-clarity for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Yuki Bansal· Sep 25, 2024

    Registry listing for requirements-clarity matched our evaluation — installs cleanly and behaves as described in the markdown.

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