Changes: - Migrate from .claude/skills/ to .claude/plugins/ structure - Add claude.json plugin metadata - Create instructions.md with all English prompts (no Chinese) - Update README.md for plugin distribution - Update .gitignore to allow .claude/plugins/ Plugin structure: - claude.json: Plugin metadata (name, version, components) - instructions.md: Main skill prompt (100% English) - README.md: Plugin documentation and usage guide Maintains all functionality: - 100-point scoring system - Iterative clarification (≥90 threshold) - PRD generation with 4 sections - Auto-activation on vague requirements Fixes #17 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
8.7 KiB
Requirements Clarity Plugin
Overview
This Claude Code plugin automatically detects vague requirements and transforms them into crystal-clear Product Requirements Documents (PRDs) through systematic clarification.
Plugin vs Skill vs Command:
- Plugin: Distributable package with metadata (
claude.json) - Skill: Auto-activated behavior (part of plugin)
- Command: Manual invocation (deprecated in favor of plugin)
Installation
/plugin install requirements-clarity
Or add to your .clauderc:
{
"plugins": {
"requirements-clarity": {
"enabled": true
}
}
}
How It Works
Automatic Activation
The plugin activates when Claude detects:
-
Vague Feature Requests
User: "add login feature" User: "implement payment system" User: "create user dashboard" -
Missing Technical Details
- No technology stack mentioned
- No architecture or constraints specified
- No integration points identified
-
Incomplete Specifications
- No acceptance criteria
- No success metrics
- No edge cases or error handling
-
Ambiguous Scope
- Unclear boundaries ("user management" - what exactly?)
- No distinction between MVP and future features
Clarification Process
User: "I want to implement a user login feature"
↓
Claude detects vague requirement
↓
Auto-activates requirements-clarity skill
↓
Initial assessment: 35/100 clarity score
↓
Round 1: Ask 2-3 targeted questions
↓
User responds
↓
Score update: 35 → 72
↓
Round 2: Continue clarifying gaps
↓
User responds
↓
Score update: 72 → 93 ✓ (≥90 threshold)
↓
Generate PRD files:
- ./.claude/specs/user-login/prd.md
- ./.claude/specs/user-login/clarification-log.md
Scoring System (100 points)
| Dimension | Points | Criteria |
|---|---|---|
| Functional Clarity | 30 | Clear inputs/outputs (10), User interaction (10), Success criteria (10) |
| Technical Specificity | 25 | Tech stack (8), Integration points (8), Constraints (9) |
| Implementation Completeness | 25 | Edge cases (8), Error handling (9), Data validation (8) |
| Business Context | 20 | Problem statement (7), Target users (7), Success metrics (6) |
Threshold: ≥ 90 points required before PRD generation
Output Structure
1. Clarification Log
./.claude/specs/{feature-name}/clarification-log.md
Documents the entire clarification conversation:
- Original requirement
- Each round of questions and answers
- Score progression
- Final assessment breakdown
2. Product Requirements Document
./.claude/specs/{feature-name}/prd.md
Structured PRD with four main sections:
Requirements Description
- Background: Business problem, target users, value proposition
- Feature Overview: Core functionality, boundaries, user scenarios
- Detailed Requirements: Inputs/outputs, interactions, data, edge cases
Design Decisions
- Technical Approach: Architecture, components, data storage, APIs
- Constraints: Performance, compatibility, security, scalability
- Risk Assessment: Technical, dependency, timeline risks
Acceptance Criteria
- Functional: Checklistable feature requirements
- Quality Standards: Code quality, testing, performance, security
- User Acceptance: UX, documentation, training
Execution Phases
- Phase 1: Preparation - Environment setup
- Phase 2: Core Development - Core implementation
- Phase 3: Integration & Testing - QA
- Phase 4: Deployment - Release
Testing Guide
Test Case 1: Vague Login Feature
Input:
"I want to implement a user login feature"
Expected Behavior:
- Claude detects vague requirement
- Announces activation of requirements-clarity skill
- Shows initial score (~30-40/100)
- Asks 2-3 questions about:
- Login method (username+password, phone+OTP, OAuth?)
- Functional scope (remember me, forgot password?)
- Technology stack (backend language, database, auth method?)
Expected Output:
- Score improves to ~70+ after round 1
- Additional questions about security, error handling, performance
- Final score ≥ 90
- PRD generated in
./.claude/specs/user-login/
Test Case 2: Ambiguous E-commerce Feature
Input:
"add shopping cart to the website"
Expected Behavior:
- Auto-activation (no tech stack, no UX details, no constraints)
- Questions about:
- Cart behavior (guest checkout? save for later? quantity limits?)
- User experience (inline cart vs dedicated page?)
- Backend integration (existing inventory system? payment gateway?)
- Data persistence (session storage, database, local storage?)
Expected Output:
- Iterative clarification (2-3 rounds)
- Score progression: ~25 → ~65 → ~92
- PRD with concrete shopping cart specifications
Test Case 3: Technical Implementation Request
Input:
"Refactor the authentication service to use JWT tokens"
Expected Behavior:
- May NOT activate (already fairly specific)
- If activates, asks about:
- Token expiration strategy
- Refresh token implementation
- Migration plan from existing auth
- Backward compatibility requirements
Test Case 4: Clear Requirement (Should NOT Activate)
Input:
"Fix the null pointer exception in auth.go line 45 by adding a nil check before accessing user.Email"
Expected Behavior:
- Skill does NOT activate (requirement is already clear)
- Claude proceeds directly to implementation
Benefits
- Proactive Quality Gate: Prevents unclear specs from proceeding to implementation
- Zero Friction: Users describe features naturally, no command syntax needed
- Context Awareness: Claude recognizes ambiguity patterns automatically
- Persistent Mode: Stays active throughout clarification conversation
- Better UX: Natural conversation flow vs explicit command invocation
Configuration
No configuration needed - the plugin is automatically discovered by Claude Code when installed.
Plugin Metadata (in claude.json):
{
"name": "requirements-clarity",
"version": "1.0.0",
"description": "Automatically clarify vague requirements into actionable PRDs",
"components": {
"skills": ["requirements-clarity"]
}
}
Troubleshooting
Plugin Not Activating
Problem: Claude doesn't enter clarification mode for vague requirements
Solutions:
- Verify plugin is installed:
/plugin list - Check plugin is enabled in
.clauderc - Ensure
instructions.mdexists in plugin directory - Try more explicit vague requirement: "add user feature"
Premature PRD Generation
Problem: PRD generated before score reaches 90
Solution: This is a bug - instructions.md explicitly requires ≥90 threshold. Review the clarification log to see actual score.
Over-Clarification
Problem: Claude asks too many questions for simple features
Expected: This is by design - better to over-clarify than under-specify. If the requirement is truly simple, answer questions quickly to reach 90+ score faster.
Examples
Example 1: Login Feature (Full Flow)
See full example in instructions.md under "Example Clarification Flow"
Summary:
- Input: "I want to implement a user login feature"
- Round 1: Login method, scope, tech stack → Score 35→72
- Round 2: Security, error handling, performance → Score 72→93
- Output: Complete PRD with bcrypt, JWT, PostgreSQL, Go backend
Example 2: API Endpoint
Input: "create an API to get user profile"
Round 1 (Score: 28/100):
Q1: What information should the API return? (name, email, avatar, preferences?)
Q2: Authentication required? (JWT, session, API key?)
Q3: Response format? (JSON, XML?) Any pagination?
Round 2 (Score: 75/100):
Q1: Error handling: What if user not found? (404, custom error?)
Q2: Performance: Caching strategy? Expected QPS?
Q3: Privacy: Any fields that should be filtered based on requester?
Round 3 (Score: 91/100):
PRD Generated:
- Endpoint: GET /api/v1/users/:id
- Auth: JWT required
- Response: JSON with name, email, avatar, bio
- Caching: Redis, 5min TTL
- Rate limit: 100 req/min per user
References
- Claude Code Plugins Documentation: https://docs.claude.com/en/docs/claude-code/plugins
- Original
/clarifCommand:development-essentials/commands/clarif.md - Original Clarification Agent:
development-essentials/agents/clarif-agent.md
Changelog
v1.0.0 (2025-10-21)
- Converted skill to plugin format
- Added
claude.jsonplugin metadata - Translated all prompts to English (was mixed Chinese/English)
- Updated documentation for plugin distribution
- Maintained 100-point scoring system and PRD structure
- Compatible with Claude Code plugin system
License: MIT
Author: stellarlink
Homepage: https://github.com/cexll/myclaude