Menu
Backend development specialist covering API design, database integration, microservices architecture, and modern backend patterns. Use when designing APIs, implementing server logic, authentication, or authorization.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Intent-First design craft specialist covering design direction, domain vocabulary, design memory, and post-build critique. Use when establishing design intent or auditing code against design principles.
Design tool integration specialist covering Figma MCP, Pencil renderer, and Pencil-to-code export. Use when fetching design context from Figma, rendering Pencil designs, or exporting to React/Tailwind code.
Documentation generation patterns for technical specs, API docs, user guides, and knowledge bases using real tools like Sphinx, MkDocs, TypeDoc, and Nextra. Use when creating docs from code, building doc sites, or automating documentation workflows.
Brand-aligned visual design system specialist for web projects. Enforces hero-first layout chaining, WCAG 2.1 AA accessibility, Lighthouse >= 80, and design token extraction from brand identity files. Covers color palettes, typography, spacing, and component specifications.
Brand-aligned copywriting specialist for marketing and product text. Enforces brand voice, anti-AI-slop rules, concrete numbers, and JSON section structure for downstream agent consumption. Covers hero, features, social_proof, cta, and footer sections with A/B variant output.
Database specialist covering PostgreSQL, MongoDB, Redis, Oracle, and advanced data patterns for modern applications. Use for database schema design, query optimization, indexing strategies, or data modeling.
| name | moai-domain-backend |
| description | Backend development specialist covering API design, database integration, microservices architecture, and modern backend patterns. Use when designing APIs, implementing server logic, authentication, or authorization. |
| license | Apache-2.0 |
| compatibility | Designed for Claude Code |
| allowed-tools | Read, Write, Edit, Bash(npm:*), Bash(npx:*), Bash(node:*), Bash(uv:*), Bash(pip:*), Bash(pytest:*), Bash(ruff:*), Bash(docker:*), Bash(curl:*), Bash(go:*), Bash(cargo:*), Grep, Glob, mcp__context7__resolve-library-id, mcp__context7__get-library-docs |
| user-invocable | false |
| metadata | {"version":"1.0.0","category":"domain","status":"active","updated":"2026-01-11","modularized":"false","tags":"backend, api, database, microservices, architecture","author":"MoAI-ADK Team"} |
| triggers | {"keywords":["backend","API","server","authentication","authorization","REST","GraphQL","gRPC","microservices","database","endpoint","middleware","FastAPI","Express","Django","Flask","serverless","caching","Redis","PostgreSQL","MongoDB"]} |
Backend Development Mastery - Comprehensive backend development patterns covering API design, database integration, microservices, and modern architecture patterns.
Core Capabilities:
When to Use:
RESTful API Architecture:
Create a FastAPI application with authentication and response models. Define a Pydantic UserResponse model with id, email, and name fields. Implement list_users and create_user endpoints with HTTPBearer security dependency. The list endpoint returns a list of UserResponse objects, while the create endpoint accepts a UserCreate model and returns a single UserResponse.
GraphQL Implementation:
Use Strawberry to define GraphQL types. Create a User type with id, email, and name fields. Define a Query type with a users resolver that returns a list of User objects asynchronously. Generate the schema by passing the Query type to strawberry.Schema.
PostgreSQL with SQLAlchemy:
Define SQLAlchemy models using declarative_base. Create a User model with id as primary key, email as unique string, and name as string column. Configure the engine with connection pooling parameters including pool_size of 20, max_overflow of 30, and pool_pre_ping enabled for connection health checks.
MongoDB with Motor:
Create a UserService class that initializes with an AsyncIOMotorClient. Set up the database and users collection in the constructor. Create indexes for email (unique) and created_at fields. Implement create_user method that inserts a document and returns the inserted_id as string.
Service Discovery with Consul:
Create a ServiceRegistry class that connects to Consul. Implement register_service method that registers a service with name, id, port, and health check endpoint. Implement discover_service method that queries healthy services and returns list of adddess:port strings.
Event-Driven Architecture:
Create an EventBus class using aio_pika for AMQP messaging. Implement connect method to establish connection and channel. Implement publish_event method that serializes event type and data as JSON and publishes to the default exchange with routing_key matching the event type.
Redis Integration:
Create a CacheManager class with Redis connection. Implement a cache_result decorator that accepts ttl parameter. The decorator generates cache keys from function name and arguments, checks Redis for cached results, executes the function on cache miss, and stores results with expiration. Use json.loads and json.dumps for serialization.
JWT Authentication:
Create a SecurityManager class with CryptContext for bcrypt password hashing. Implement hash_password and verify_password methods using the context. Implement create_access_token that encodes a JWT with expiration time using HS256 algorithm. Default expiration is 15 minutes if not specified.
Database Connection Pooling:
Create an optimized SQLAlchemy engine with QueuePool, pool_size 20, max_overflow 30, pool_pre_ping enabled, and pool_recycle of 3600 seconds. Add event listeners for before_cursor_execute and after_cursor_execute to track query timing. Log warnings for queries exceeding 100ms threshold.
Primary Technologies:
Integration Patterns:
For working code examples, see examples.md.
Status: Production Ready Last Updated: 2026-01-11 Maintained by: MoAI-ADK Backend Team
| Rationalization | Reality |
|---|---|
| "Input validation can happen on the frontend" | Frontend validation is UX. Backend validation is security. They serve different purposes and both are required. |
| "This endpoint is internal, it does not need authentication" | Internal endpoints are reachable from compromised services. Zero-trust means every endpoint validates identity. |
| "I will add error handling later" | Unhandled errors leak stack traces, connection strings, and internal state. Error handling is day-one work. |
| "The ORM handles SQL injection" | ORMs protect parameterized queries. Raw queries, dynamic filters, and ORDER BY clauses still need escaping. |
| "This API is backward-compatible, no version bump needed" | Removing optional fields, changing defaults, or altering error formats are breaking changes to existing callers. |
| "Microservices are overkill, I will just add another endpoint" | Unbounded endpoint growth creates a monolith-in-disguise. Evaluate service boundaries before adding. |
Hyrum's Law: With a sufficient number of users, every observable behavior of your API will be depended on by somebody. Changing anything, no matter how trivial, can break someone.
