Backend Development Feature Development

Orchestrate end-to-end feature development from requirements to production deployment:

[Extended thinking: This workflow orchestrates specialized agents through comprehensive feature development phases - from discovery and planning through implementation, testing, and deployment. Each phase builds on previous outputs, ensuring coherent feature delivery. The workflow supports multiple development methodologies (traditional, TDD/BDD, DDD), feature complexity levels, and modern deployment strategies including feature flags, gradual rollouts, and observability-first development. Agents receive detailed context from previous phases to maintain consistency and quality throughout the development lifecycle.]

Use this skill when

• Coordinating end-to-end feature delivery across backend, frontend, and data
• Managing requirements, architecture, implementation, testing, and rollout
• Planning multi-service changes with deployment and monitoring needs
• Aligning teams on scope, risks, and success metrics

Do not use this skill when

• The task is a small, isolated backend change or bug fix
• You only need a single specialist task, not a full workflow
• There is no deployment or cross-team coordination involved

Instructions

1. Confirm feature scope, success metrics, and constraints.
2. Select a methodology and define phase outputs.
3. Orchestrate implementation, testing, and security validation.
4. Prepare rollout, monitoring, and documentation plans.

Safety

• Avoid production changes without approvals and rollback plans.
• Validate data migrations and feature flags in staging first.

Configuration Options

Development Methodology

• traditional: Sequential development with testing after implementation
• tdd: Test-Driven Development with red-green-refactor cycles
• bdd: Behavior-Driven Development with scenario-based testing
• ddd: Domain-Driven Design with bounded contexts and aggregates

Feature Complexity

• simple: Single service, minimal integration (1-2 days)
• medium: Multiple services, moderate integration (3-5 days)
• complex: Cross-domain, extensive integration (1-2 weeks)
• epic: Major architectural changes, multiple teams (2+ weeks)

Deployment Strategy

• direct: Immediate rollout to all users
• canary: Gradual rollout starting with 5% of traffic
• feature-flag: Controlled activation via feature toggles
• blue-green: Zero-downtime deployment with instant rollback
• a-b-test: Split traffic for experimentation and metrics

Phase 1: Discovery & Requirements Planning

1. Business Analysis & Requirements

   • Use Task tool with subagent_type="business-analytics::business-analyst"
   • Prompt: "Analyze feature requirements for: $ARGUMENTS. Define user stories, acceptance criteria, success metrics, and business value. Identify stakeholders, dependencies, and risks. Create feature specification document with clear scope boundaries."
   • Expected output: Requirements document with user stories, success metrics, risk assessment
   • Context: Initial feature request and business context

2. Technical Architecture Design

   • Use Task tool with subagent_type="comprehensive-review::architect-review"
   • Prompt: "Design technical architecture for feature: $ARGUMENTS. Using requirements: [include business analysis from step 1]. Define service boundaries, API contracts, data models, integration points, and technology stack. Consider scalability, performance, and security requirements."
   • Expected output: Technical design document with architecture diagrams, API specifications, data models
   • Context: Business requirements, existing system architecture

3. Feasibility & Risk Assessment

   • Use Task tool with subagent_type="security-scanning::security-auditor"
   • Prompt: "Assess security implications and risks for feature: $ARGUMENTS. Review architecture: [include technical design from step 2]. Identify security requirements, compliance needs, data privacy concerns, and potential vulnerabilities."
   • Expected output: Security assessment with risk matrix, compliance checklist, mitigation strategies
   • Context: Technical design, regulatory requirements

Phase 2: Implementation & Development

4. Backend Services Implementation

   • Use Task tool with subagent_type="backend-architect"
   • Prompt: "Implement backend services for: $ARGUMENTS. Follow technical design: [include architecture from step 2]. Build RESTful/GraphQL APIs, implement business logic, integrate with data layer, add resilience patterns (circuit breakers, retries), implement caching strategies. Include feature flags for gradual rollout."
   • Expected output: Backend services with APIs, business logic, database integration, feature flags
   • Context: Technical design, API contracts, data models

5. Frontend Implementation

   • Use Task tool with subagent_type="frontend-mobile-development::frontend-developer"
   • Prompt: "Build frontend components for: $ARGUMENTS. Integrate with backend APIs: [include API endpoints from step 4]. Implement responsive UI, state management, error handling, loading states, and analytics tracking. Add feature flag integration for A/B testing capabilities."
   • Expected output: Frontend components with API integration, state management, analytics
   • Context: Backend APIs, UI/UX designs, user stories

6. Data Pipeline & Integration

   • Use Task tool with subagent_type="data-engineering::data-engineer"
   • Prompt: "Build data pipelines for: $ARGUMENTS. Design ETL/ELT processes, implement data validation, create analytics events, set up data quality monitoring. Integrate with product analytics platforms for feature usage tracking."
   • Expected output: Data pipelines, analytics events, data quality checks
   • Context: Data requirements, analytics needs, existing data infrastructure

Phase 3: Testing & Quality Assurance

7. Automated Test Suite

   • Use Task tool with subagent_type="unit-testing::test-automator"
   • Prompt: "Create comprehensive test suite for: $ARGUMENTS. Write unit tests for backend: [from step 4] and frontend: [from step 5]. Add integration tests for API endpoints, E2E tests for critical user journeys, performance tests for scalability validation. Ensure minimum 80% code coverage."
   • Expected output: Test suites with unit, integration, E2E, and performance tests
   • Context: Implementation code, acceptance criteria, test requirements

8. Security Validation

   • Use Task tool with subagent_type="security-scanning::security-auditor"
   • Prompt: "Perform security testing for: $ARGUMENTS. Review implementation: [include backend and frontend from steps 4-5]. Run OWASP checks, penetration testing, dependency scanning, and compliance validation. Verify data encryption, authentication, and authorization."
   • Expected output: Security test results, vulnerability report, remediation actions
   • Context: Implementation code, security requirements

9. Performance Optimization

   • Use Task tool with subagent_type="application-performance::performance-engineer"
   • Prompt: "Optimize performance for: $ARGUMENTS. Analyze backend services: [from step 4] and frontend: [from step 5]. Profile code, optimize queries, implement caching, reduce bundle sizes, improve load times. Set up performance budgets and monitoring."
   • Expected output: Performance improvements, optimization report, performance metrics
   • Context: Implementation code, performance requirements

Phase 4: Deployment & Monitoring

10. Deployment Strategy & Pipeline

    • Use Task tool with subagent_type="deployment-strategies::deployment-engineer"
    • Prompt: "Prepare deployment for: $ARGUMENTS. Create CI/CD pipeline with automated tests: [from step 7]. Configure feature flags for gradual rollout, implement blue-green deployment, set up rollback procedures. Create deployment runbook and rollback plan."
    • Expected output: CI/CD pipeline, deployment configuration, rollback procedures
    • Context: Test suites, infrastructure requirements, deployment strategy

11. Observability & Monitoring

    • Use Task tool with subagent_type="observability-monitoring::observability-engineer"
    • Prompt: "Set up observability for: $ARGUMENTS. Implement distributed tracing, custom metrics, error tracking, and alerting. Create dashboards for feature usage, performance metrics, error rates, and business KPIs. Set up SLOs/SLIs with automated alerts."
    • Expected output: Monitoring dashboards, alerts, SLO definitions, observability infrastructure
    • Context: Feature implementation, success metrics, operational requirements

12. Documentation & Knowledge Transfer

    • Use Task tool with subagent_type="documentation-generation::docs-architect"
    • Prompt: "Generate comprehensive documentation for: $ARGUMENTS. Create API documentation, user guides, deployment guides, troubleshooting runbooks. Include architecture diagrams, data flow diagrams, and integration guides. Generate automated changelog from commits."
    • Expected output: API docs, user guides, runbooks, architecture documentation
    • Context: All previous phases' outputs

Execution Parameters

Required Parameters

• --feature: Feature name and description
• --methodology: Development approach (traditional|tdd|bdd|ddd)
• --complexity: Feature complexity level (simple|medium|complex|epic)

Optional Parameters

• --deployment-strategy: Deployment approach (direct|canary|feature-flag|blue-green|a-b-test)
• --test-coverage-min: Minimum test coverage threshold (default: 80%)
• --performance-budget: Performance requirements (e.g., <200ms response time)
• --rollout-percentage: Initial rollout percentage for gradual deployment (default: 5%)
• --feature-flag-service: Feature flag provider (launchdarkly|split|unleash|custom)
• --analytics-platform: Analytics integration (segment|amplitude|mixpanel|custom)
• --monitoring-stack: Observability tools (datadog|newrelic|grafana|custom)

Success Criteria

• All acceptance criteria from business requirements are met
• Test coverage exceeds minimum threshold (80% default)
• Security scan shows no critical vulnerabilities
• Performance meets defined budgets and SLOs
• Feature flags configured for controlled rollout
• Monitoring and alerting fully operational
• Documentation complete and approved
• Successful deployment to production with rollback capability
• Product analytics tracking feature usage
• A/B test metrics configured (if applicable)

Rollback Strategy

If issues arise during or after deployment:

1. Immediate feature flag disable (< 1 minute)
2. Blue-green traffic switch (< 5 minutes)
3. Full deployment rollback via CI/CD (< 15 minutes)
4. Database migration rollback if needed (coordinate with data team)
5. Incident post-mortem and fixes before re-deployment

Feature description: $ARGUMENTS

AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Retrieve prior API design decisions, database schema choices, and error handling patterns. Cache API response templates for consistent error formatting.

# Check for prior backend/API context before starting
python3 execution/memory_manager.py auto --query "API design patterns and architecture decisions for Backend Development Feature Development"

Storing Results

After completing work, store backend/API decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "API architecture: REST with HATEOAS, JWT auth, rate limiting at 100 req/min per tenant" \
  --type decision --project <project> \
  --tags backend-development-feature-development backend

Multi-Agent Collaboration

Share API contract changes with frontend agents so they update their client code, and with QA agents for test coverage.

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Implemented API endpoints — 5 new routes with OpenAPI spec and integration tests" \
  --project <project>

Agent Team: Code Review

After implementation, dispatch code_review_team for two-stage review (spec compliance + code quality) before merging.

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