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Found 68 Skills
Review Kafka producer and consumer performance configurations in both the live cluster (via Lenses MCP) and the codebase. Flags un-tuned defaults, anti-patterns and missing best practices. Use when user says "review Kafka performance", "check producer configs", "tune Kafka settings" or asks about throughput, batching or compression. Do NOT use for cluster sizing or capacity planning.
Debugs why session recordings aren't appearing in the local dev environment. Use when a developer reports that local replay ingestion isn't working, recordings aren't showing up despite /s calls, or the replay pipeline seems broken after hogli start. Covers the full local pipeline: SDK capture, Caddy proxy, capture-replay (Rust), Kafka, ingestion-sessionreplay (Node), recording-api (Node), SeaweedFS, and common failure modes like orphaned processes, stuck phrocs workers, and trigger misconfiguration.
Architect, build, and debug Kafka Streams apps (JVM-embedded stream processing). Use when user mentions KStream, KTable, topology, TopologyTestDriver, StreamsBuilder, interactive queries, GlobalKTable, joins/windows/aggregations, or debugging issues (rebalancing, state stores, lag, deserialization errors). Also use when user wants to optimize Kafka Streams for WarpStream or tune Kafka Streams client configuration for WarpStream. Do NOT trigger for Flink, connectors, CDC, or plain producer/consumer.
DigitalOcean Managed Databases for PostgreSQL, MySQL, Redis, MongoDB, Kafka, OpenSearch, and Valkey. Use when provisioning, scaling, or operating managed database clusters on DigitalOcean.
Manages MongoDB Atlas Stream Processing (ASP) workflows. Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations for streaming data workloads and event processing. NOT for general MongoDB queries or Atlas cluster management. Requires MongoDB MCP Server with Atlas API credentials.
Complete Java Spring Boot skill set for building enterprise applications. Includes modular architecture with optional components: - PostgreSQL database with JPA/Hibernate + Flyway migration - Redis caching (optional) - Kafka/RabbitMQ messaging (optional, choose one) - JWT + OAuth2 authentication (optional OAuth2) - RBAC authorization (optional) - TDD with Mockito - Spec-First Development with OpenSpec
Create or evaluate an architecture decision record (ADR). Use when choosing between technologies (e.g., Kafka vs SQS), documenting a design decision with trade-offs and consequences, reviewing a system design proposal, or designing a new component from requirements and constraints.
Routes PubNub events to external systems with no code via Events & Actions (E&A). Covers event listeners (Messages, Users, Channels, Push, Memberships), action targets (Webhook, SQS, Kinesis, S3, Kafka, IFTTT, AMQP), filter types (basic vs JSONPath), retry policy, envelopes, and batching. Use when integrating PubNub with Lambda, Kafka, SQS, S3, EventBridge, an analytics pipeline, or any external system.
Complete E2E (end-to-end) and integration testing skill for TypeScript/NestJS projects using Jest, real infrastructure via Docker, and GWT pattern. ALWAYS use this skill when user needs to: **SETUP** - Initialize or configure E2E testing infrastructure: - Set up E2E testing for a new project - Configure docker-compose for testing (Kafka, PostgreSQL, MongoDB, Redis) - Create jest-e2e.config.ts or E2E Jest configuration - Set up test helpers for database, Kafka, or Redis - Configure .env.e2e environment variables - Create test/e2e directory structure **WRITE** - Create or add E2E/integration tests: - Write, create, add, or generate e2e tests or integration tests - Test API endpoints, workflows, or complete features end-to-end - Test with real databases, message brokers, or external services - Test Kafka consumers/producers, event-driven workflows - Working on any file ending in .e2e-spec.ts or in test/e2e/ directory - Use GWT (Given-When-Then) pattern for tests **REVIEW** - Audit or evaluate E2E tests: - Review existing E2E tests for quality - Check test isolation and cleanup patterns - Audit GWT pattern compliance - Evaluate assertion quality and specificity - Check for anti-patterns (multiple WHEN actions, conditional assertions) **RUN** - Execute or analyze E2E test results: - Run E2E tests - Start/stop Docker infrastructure for testing - Analyze E2E test results - Verify Docker services are healthy - Interpret test output and failures **DEBUG** - Fix failing or flaky E2E tests: - Fix failing E2E tests - Debug flaky tests or test isolation issues - Troubleshoot connection errors (database, Kafka, Redis) - Fix timeout issues or async operation failures - Diagnose race conditions or state leakage - Debug Kafka message consumption issues **OPTIMIZE** - Improve E2E test performance: - Speed up slow E2E tests - Optimize Docker infrastructure startup - Replace fixed waits with smart polling - Reduce beforeEach cleanup time - Improve test parallelization where safe Keywords: e2e, end-to-end, integration test, e2e-spec.ts, test/e2e, Jest, supertest, NestJS, Kafka, Redpanda, PostgreSQL, MongoDB, Redis, docker-compose, GWT pattern, Given-When-Then, real infrastructure, test isolation, flaky test, MSW, nock, waitForMessages, fix e2e, debug e2e, run e2e, review e2e, optimize e2e, setup e2e
Implement distributed transactions using the Saga Pattern in Spring Boot microservices. Use when building microservices requiring transaction management across multiple services, handling compensating transactions, ensuring eventual consistency, or implementing choreography or orchestration-based sagas with Spring Boot, Kafka, or Axon Framework.
Comprehensive plugin for SAP Datasphere development with 3 specialized agents, 5 slash commands, and validation hooks. Use when building data warehouses on SAP BTP, creating analytic models, configuring data flows and replication flows, setting up connections to SAP and third-party systems, managing spaces and users, implementing data access controls, using the datasphere CLI, creating data products for the marketplace, or monitoring data integration tasks. Covers Data Builder (graphical/SQL views, local/remote tables, transformation flows), Business Builder (business entities, consumption models), analytic models (dimensions, measures, hierarchies), 40+ connection types (SAP S/4HANA, BW/4HANA, HANA Cloud, AWS, Azure, GCP, Kafka, Generic HTTP), real-time replication, task chains, content transport, CLI automation, catalog governance, and data marketplace. Includes 2025 features: Generic HTTP connections, REST API tasks in task chains, SAP Business Data Cloud integration. Keywords: sap datasphere, data warehouse cloud, dwc, data builder, business builder, analytic model, graphical view, sql view, transformation flow, replication flow, data flow, task chain, remote table, local table, sap btp data warehouse, datasphere connection, datasphere space, data access control, elastic compute node, sap analytics cloud integration, datasphere cli, data products, data marketplace, catalog, governance
Data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data modeling, pipeline orchestration, data quality, and DataOps. Use when designing data architectures, building data pipelines, optimizing data workflows, implementing data governance, or troubleshooting data issues.