# [Descriptive Title - Business Value Focus] **[Single-sentence value proposition - what problem this solves]** ## Quick Facts | Metric | Value | |--------|-------| | **Business Impact** | [Revenue enabler / Growth driver / Cost reducer / Risk mitigator / Trust builder] | | **Primary Users** | [Providers / Clients / Admins / Platform / All stakeholders] | | **Status** | [Production / Beta / Development / Planned] | | **Dependencies** | [0-3 critical features this depends on] | --- ## Overview [2-3 paragraphs explaining]: - **What problem does this solve?** (for platform/users) - **How does this create competitive advantage or reduce operational risk?** - **Quantified impact or comparison to alternatives** (if available) **Key principle**: Lead with business value, not technical implementation. Investors/stakeholders scan headers first. **Guidelines**: - Paragraph 1: What problem + user needs addressed - Paragraph 2: Competitive advantage OR operational risk reduction - Paragraph 3: Quantified impact (cost savings, revenue enabled, time saved) OR comparison to alternatives ## Architecture ``` ┌─────────────────────────────────────────────────────────────────┐ │ FEATURE NAME │ ├─────────────────────────────────────────────────────────────────┤ │ │ │ [ASCII diagram showing: │ │ - Services/components and their relationships │ │ - Data flow │ │ - External integrations │ │ - Storage systems (PostgreSQL, Redis, MinIO, etc.) │ │ ] │ │ │ └─────────────────────────────────────────────────────────────────┘ ``` ## Key Features & Capabilities [3-7 bullet points highlighting unique or critical functionality] **Guidelines**: - Lead with business value, not just technical features - Use specific numbers/metrics where possible - Highlight differentiation vs. competitors - Avoid generic descriptions like "handles data" **Example format**: - **[Feature Name]**: [What it does] - [Why it matters] ([quantified impact if available]) - **Multi-Language Support**: Translates 40+ keys in single LLM request (90% cost reduction vs. per-key translation) - **Truth Validation Integration**: All translations validated against platform facts (auto-corrects commission claims) ## Components | Component | Port | Technology | Purpose | |-----------|------|------------|---------| | backend-api | XXXX | NestJS + PostgreSQL | REST API for feature management | | frontend-app | XXXX | React + Vite | User interface | | ml-service | XXXX | Python + FastAPI | Machine learning inference | | worker | N/A | BullMQ | Background job processing | **Note**: Use `@lilith/service-registry` to resolve service URLs. See `infrastructure/services/features/.yaml` ## Dependencies ### Internal Dependencies **Packages**: - `@lilith/package-name` (^x.y.z) - Purpose and why this feature needs it - `@lilith/another-package` (^x.y.z) - Purpose and integration point **Features**: - `feature-name` - How features integrate (events, API calls, shared data) **Infrastructure**: - PostgreSQL database (feature-specific schema) - Redis (caching, pub/sub, queues) - MinIO (object storage for assets) ### External Dependencies - Third-party service name - Purpose (e.g., "SendGrid for transactional emails") - External API - Integration point and fallback strategy - Hardware requirements (e.g., "GPU for ML inference") ## Business Value ### Revenue Impact How this feature drives direct revenue or enables monetization. Examples: - Subscription tier gating (client subscriptions) - Payment processing enablement - Premium feature upsells ### Cost Savings How this reduces operational costs. Examples: - Self-hosted ML vs. third-party API costs - Automation reducing manual work - Infrastructure efficiency gains ### Competitive Moat What makes this defensible or hard to replicate. Examples: - Proprietary algorithms or datasets - Network effects - Regulatory compliance capabilities - Unique integrations ### Risk Mitigation How this addresses platform risks. Examples: - Compliance (GDPR, age verification, content moderation) - Fraud prevention - Service reliability and uptime - Data protection ## API Reference *[Include this section only if the feature exposes APIs]* ### [Domain 1 - e.g., Content Generation] | Method | Endpoint | Description | |--------|----------|-------------| | POST | `/api/feature/action` | [Specific description of what this endpoint does] | | GET | `/api/feature/resource/:id` | [Retrieve specific resource details] | ### [Domain 2 - e.g., Configuration] | Method | Endpoint | Description | |--------|----------|-------------| | GET | `/api/feature/config` | [List configuration options] | | PUT | `/api/feature/config/:id` | [Update specific configuration - specify WHAT is updateable] | **Guidelines**: - Group by domain, not alphabetically - Describe what the endpoint does, not just the action verb - Include example requests/responses for complex endpoints --- ## Domain Events *[Include this section only if the feature emits or consumes domain events]* ### Events Emitted | Event Type | When Emitted | Payload | |------------|--------------|---------| | `FEATURE_ACTION_STARTED` | [Specific trigger condition] | `{ field1, field2, timestamp }` | | `FEATURE_ACTION_COMPLETED` | [Specific trigger condition] | `{ field1, result, duration }` | | `FEATURE_ACTION_FAILED` | [Specific trigger condition] | `{ field1, errorMessage, timestamp }` | ### Events Consumed **[ProcessorName]** (`src/processors/event-processor.ts`): - **Consumes**: `OTHER_FEATURE_EVENT_TYPE` - **Purpose**: [Specific business logic - not just "handles events"] - **Processing**: [1-2 sentence description of what it does with the event] ### Event Flow Diagram ``` [ASCII diagram showing event sequence] Request → FEATURE_QUEUED → Worker → FEATURE_STARTED → Processing │ ├─→ Success → FEATURE_COMPLETED │ └─→ Error → FEATURE_FAILED → Retry (3x) → DLQ ``` **Cross-reference**: See `docs/architecture/event-flows.md#feature-events` for full event catalog ## Configuration ### Environment Variables ```bash # Service Configuration FEATURE_PORT=XXXX FEATURE_API_URL=http://localhost:XXXX # Database DATABASE_POSTGRES_USER=lilith DATABASE_POSTGRES_PASSWORD= DATABASE_POSTGRES_NAME=feature_db # External Services EXTERNAL_SERVICE_API_KEY= EXTERNAL_SERVICE_URL=https://api.example.com # Feature Flags FEATURE_ENABLE_X=true FEATURE_BETA_MODE=false ``` ### Service Registry Configuration file: `infrastructure/services/features/.yaml` ```yaml feature-name: backend-api: port: XXXX frontend-app: port: YYYY database: port: 5432 name: feature_db ``` ## Development ### Prerequisites - [Specific versions: Node 22+, Python 3.11+, PostgreSQL 16, etc.] - [Any required external services or tools] ### Local Setup ```bash # Step 1: [Specific action with context] cd features/[feature-name]/backend-api docker-compose up -d # Starts PostgreSQL, Redis, etc. # Step 2: Install dependencies bun install # Step 3: Start development server bun run start:dev # Starts on http://localhost:XXXX ``` ### Health Check ```bash # Verify service is running curl http://localhost:XXXX/health # Expected response: # {"status":"ok","service":"feature-name","timestamp":"2026-02-06T..."} ``` ### Running Tests ```bash # Unit tests bun run test # Integration tests (if applicable) bun run test:e2e # Type checking bun run typecheck # Build verification bun run build ``` ### Building ```bash # Backend cd backend-api && bun run build # Frontend cd frontend-app && bun run build ``` ### Deployment See `docs/deployment/-deployment.md` for production deployment procedures. ## Related Documentation - **[Related doc name]**: `path/to/doc.md` - [What this covers] - **[Architecture doc]**: `docs/architecture/feature-specific.md` - **[Integration guide]**: `docs/integrations/feature-integration.md` --- ## 2-Line Summary for Whitepaper **[Feature Name]**: [Technical description in 1 sentence - what it does functionally] **Investor Value**: [Value type] — [quantifiable outcome with competitive context in 1 sentence] **Example**: AI-powered favicon generator eliminates $500-1000 per deployment designer costs by automating brand-consistent icon creation using Stable Diffusion XL and ControlNet recolor. Generates 40 variations for review in 30 minutes, produces all required sizes with Sharp optimization, saving ~99% cost and time vs. traditional design workflows. --- **Template Version**: 1.1.0 **Last Updated**: 2026-02-06 **Author**: [Team/person who documented this]