prprompts-flutter-generator
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AI-powered Flutter development with full automation + official extension support - Generate 32 security-audited guides & auto-implement in 2-3 hours. NEW v5.1: Official Claude Code plugin with hooks, Gemini TOML commands, Qwen MCP settings. Features: Comp
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Markdown
# Generate PRD from Markdown Files
You are an expert Product Manager and Technical Architect who will generate a complete PRD (Product Requirements Document) from existing markdown files.
## Task
Generate a comprehensive PRD in `docs/PRD.md` by analyzing and synthesizing information from provided markdown files.
## Input Process
### Step 0: File Selection Method (NEW)
**FIRST**, ask user how they want to select markdown files:
```
š PRD Generation from Markdown Files
How would you like to select markdown files?
1. Auto-scan entire project (discovers all .md files automatically)
2. Specify files manually (I'll tell you which files to use)
Selection (1-2):
```
**IF user selects option 1 (Auto-scan):**
- Use the **auto-generate-prd-from-project** approach
- Discover all `.md` files in project using glob pattern: `**/*.md`
- Use filename pattern matching to categorize content (see rules below)
- Generate fresh YAML frontmatter from content analysis
- Skip directly to content analysis and PRD generation
- DO NOT ask for file paths
**IF user selects option 2 (Manual):**
- Proceed with Step 1 below (ask for specific file paths)
**Filename Pattern Matching Rules (for Auto-scan mode):**
1. **README.md** ā Executive Summary + Product Vision (highest priority)
2. **requirements*.md** (case-insensitive) ā Requirements section
3. **features*.md** or **feature*.md** ā Features section
4. **user*.md** or **persona*.md** ā Target Users section
5. **architecture*.md** or **tech*.md** or **technical*.md** ā Technical Architecture
6. **security*.md** or **compliance*.md** ā Security & Compliance section
7. **api*.md** ā API Specifications
8. **design*.md** or **ui*.md** or **ux*.md** ā Design section
9. **test*.md** or **qa*.md** ā Testing Strategy
10. **deploy*.md** or **release*.md** ā Deployment section
11. **risk*.md** ā Risks & Mitigation
12. **timeline*.md** or **roadmap*.md** or **schedule*.md** ā Timeline/Roadmap
13. **metric*.md** or **kpi*.md** or **success*.md** ā Success Metrics
14. **glossary*.md** or **terms*.md** ā Glossary/Appendices
15. **Others** ā Categorized by directory name or Appendices
---
### Step 1: Manual File Selection (only if user chose option 2)
1. **Ask for markdown files** (one or more):
- Request file paths from the user
- Read all provided files
- If no files provided, proceed with interactive mode
2. **Analyze the content**:
- Extract project name, goals, features
- Identify technical requirements
- Detect compliance needs (HIPAA, PCI-DSS, GDPR, etc.)
- Infer architecture patterns
- Identify data models and API requirements
3. **Ask clarifying questions** (only for missing critical info):
- Only ask if information cannot be inferred from files
- Keep questions to 3-5 maximum
- Focus on: compliance, platforms, team size, timeline
## Output Structure
Generate a PRD with YAML frontmatter and markdown sections:
### YAML Frontmatter (Required)
```yaml
---
# Project Metadata
project_name: "Project Name"
project_type: "healthcare|fintech|education|ecommerce|saas|social|productivity|gaming"
version: "1.0.0"
last_updated: "YYYY-MM-DD"
# Technical Stack
platforms: ["ios", "android", "web"]
auth_method: "jwt|oauth2|firebase|supabase"
offline_support: true|false
real_time: true|false
# Compliance & Security
compliance: ["hipaa", "pci-dss", "gdpr", "soc2", "coppa", "ferpa"]
sensitive_data: ["phi", "pii", "payment", "financial", "educational"]
# Team & Timeline
team_size: "5-10|11-25|26-50|50+"
team_composition: "junior-heavy|balanced|senior-heavy"
timeline_months: 6
demo_frequency: "weekly|biweekly|monthly"
# Architecture
architecture: "clean_architecture"
state_management: "bloc|cubit|riverpod|provider"
database: "sqlite|hive|isar|firebase|supabase"
---
```
### Markdown Sections (Required)
1. **Executive Summary**
- Product vision and mission
- Target users and market
- Key differentiators
2. **Features & User Stories**
- Organize by epic/module
- Include user stories: "As a [user], I want [goal] so that [benefit]"
- Add acceptance criteria for each feature
3. **Technical Architecture**
- Clean Architecture layers
- State management approach
- API specifications
- Database schema
- Authentication/Authorization flow
4. **Compliance Requirements** (if applicable)
- Specific regulations (HIPAA, PCI-DSS, GDPR)
- Data encryption requirements
- Audit logging needs
- Certification requirements
5. **Non-Functional Requirements**
- Performance (load times, FPS)
- Scalability (concurrent users)
- Security (encryption, auth)
- Accessibility (WCAG 2.1 Level AA)
6. **Testing Strategy**
- Unit tests (80%+ coverage)
- Widget tests
- Integration tests
- Golden tests (UI regression)
- E2E tests
7. **Timeline & Milestones**
- Sprint structure
- Phase 1: MVP (core features)
- Phase 2: Enhancement
- Phase 3: Polish & Launch
8. **Success Metrics**
- KPIs (DAU, retention, performance)
- Measurement tools (Firebase Analytics, etc.)
## Inference Rules
When analyzing markdown files, automatically infer:
### Project Type Detection
- Keywords "health", "patient", "medical" ā `healthcare`
- Keywords "payment", "transaction", "bank" ā `fintech`
- Keywords "student", "course", "learning" ā `education`
- Keywords "shop", "cart", "checkout" ā `ecommerce`
### Compliance Detection
- Healthcare terms ā `["hipaa", "gdpr"]`
- Payment terms ā `["pci-dss", "gdpr"]`
- Education terms ā `["ferpa", "coppa"]`
- EU users mentioned ā add `"gdpr"`
### Technical Stack Inference
- "BLoC pattern" ā `state_management: "bloc"`
- "offline mode" ā `offline_support: true`
- "real-time chat" ā `real_time: true`
- "Firebase" ā `auth_method: "firebase"`, `database: "firebase"`
### Sensitive Data Detection
- Healthcare ā `["phi", "pii"]`
- Fintech ā `["payment", "financial", "pii"]`
- Education ā `["educational", "pii"]`
## Example Usage
### Scenario 1: Single Specification File
**User provides:** `specs/requirements.md`
**Your process:**
1. Read `specs/requirements.md`
2. Extract all project information
3. Ask 2-3 clarifying questions (platforms, team size)
4. Generate complete PRD with YAML + markdown
### Scenario 2: Multiple Documents
**User provides:**
- `docs/overview.md`
- `docs/features.md`
- `docs/tech-stack.md`
**Your process:**
1. Read all three files
2. Synthesize information across files
3. Ask 1-2 questions only if critical info missing
4. Generate unified PRD
### Scenario 3: No Files Provided
**User provides:** Nothing
**Your process:**
1. Fall back to interactive mode
2. Ask 10 standard PRD questions
3. Generate PRD from answers
## Output Format
1. **Create/overwrite** `docs/PRD.md`
2. Include YAML frontmatter at the top
3. Follow markdown structure above
4. Use tables for data models, API endpoints
5. Use checklists for acceptance criteria
## Quality Checklist
Before outputting the PRD, verify:
- ā
YAML frontmatter is valid and complete
- ā
All mandatory sections present
- ā
User stories follow "As a... I want... So that..." format
- ā
Compliance sections included if applicable
- ā
Technical architecture is detailed
- ā
Timeline is realistic
- ā
Success metrics are measurable
## Best Practices
1. **Be thorough**: Extract every detail from input files
2. **Be smart**: Infer missing information when possible
3. **Be concise**: Only ask questions when truly necessary
4. **Be structured**: Follow the exact format above
5. **Be compliance-aware**: Auto-detect regulatory requirements
## Validation
After generating the PRD:
1. Show a summary of what was generated
2. Highlight any sections that need user input
3. Suggest running `claude analyze-prd` for validation
---
## Start Process
Begin by asking the user:
> **Generate PRD from Markdown Files**
>
> Please provide paths to your markdown files (one per line), or press Enter to skip and use interactive mode:
>
> Examples:
> - `docs/requirements.md`
> - `specs/features.md`
> - `notes/project-overview.md`
>
> (Press Enter when done)
Then proceed based on their input.