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Found 162 Skills
AWS CloudFormation patterns for Lambda functions, layers, event sources, and integrations. Use when creating Lambda functions with CloudFormation, configuring API Gateway, Step Functions, EventBridge, SQS, SNS triggers, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and best practices for cold start optimization.
AWS Lambda patterns using AWS SDK for Java 2.x. Use when invoking Lambda functions, creating/updating functions, managing function configurations, working with Lambda layers, or integrating Lambda with Spring Boot applications.
Create interactive maps with markers, heatmaps, routes, and choropleth layers. Use when visualizing geographic data, plotting locations, or creating map-based reports.
Validate at every layer data passes through to make bugs impossible. Use when invalid data causes failures deep in execution, requiring validation at multiple system layers.
AI trustworthiness testing using OWASP AI Testing Guide v1. Execute 44 test cases across 4 layers (Application, Model, Infrastructure, Data) with practical payloads and remediation.
Use when designing data ownership, validation boundaries, consistency models, or configuration strategy in Python. Also use when encountering unclear ownership across modules, shared mutable state leaking between layers, validation gaps at ingress, cross-module transactional coupling, or config drift between environments.
Enforces Effect-TS patterns for services, errors, layers, and atoms. Use when writing code with Context.Tag, Schema.TaggedError, Layer composition, or effect-atom React components.
Converts legacy SQL to modular dbt models. Use when migrating SQL to dbt for: (1) Converting stored procedures, views, or raw SQL files to dbt models (2) Task mentions "migrate", "convert", "legacy SQL", "transform to dbt", or "modernize" (3) Breaking monolithic queries into modular layers (discovers project conventions first) (4) Porting existing data pipelines or ETL to dbt patterns Checks for existing models/sources, builds and validates layer by layer.
Expert guidance for SQLAlchemy 2.0 + Pydantic + PostgreSQL. Use when setting up database layers, defining models, creating migrations, or any database-related work. Automatically activated for DB tasks.
Multi-layer caching with type-specific TTLs, get-or-generate pattern, memory and database layers, and graceful invalidation without cache stampede.
Generate Go cache implementations following GO modular architechture conventions. Use when creating cache layers in internal/modules/<module>/cache/ - user state caching, session caching, rate limiting data, temporary data storage, or any domain cache that uses Redis for fast data access with TTL support.
Generate Go repository port interfaces and implementations following GO modular architechture conventions (Gorm, PingoDB, OTEL tracing, Fx DI, ports architecture). Use when creating data access layers for entities in internal/modules/<module>/ including CRUD operations (Create, FindAll, FindByID, Update, Delete), custom queries, pagination, or transactions.