23 skills · sorted by relevance
Build or review Java services with Quarkus 3.x using patterns for REST APIs, database access with Panache, and messaging with Apache Camel. Examples cover layered code structure, validation, transactions, and asynchronous processing, where work completes separately from the main flow.
Add background jobs to Django with Celery, moving work such as email delivery and PDF generation outside web requests. Covers scheduled runs, retries, linked or parallel tasks, monitoring, and tests, with Redis or RabbitMQ carrying task messages.
You are an expert in amqplib, the Node.js client for RabbitMQ and AMQP 0-9-1 protocol. You help developers implement reliable message queuing with work queues, pub/sub fanout, topic routing, RPC patterns, dead letter queues, and message acknowledgment — building decoupled microservices that communicate asynchronously through RabbitMQ.
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Message queues, pub/sub, event sourcing with Kafka, RabbitMQ, Redis Streams. Activate on: event-driven, message queue, pub/sub, Kafka, RabbitMQ, event bus, async messaging, dead letter queue. NOT for: CQRS projections (use cqrs-event-sourcing-architect), real-time WebSocket (use websocket-realtime-expert), observability (use observability-apm-expert).
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Message queues, pub/sub, event sourcing with Kafka, RabbitMQ, Redis Streams. Activate on: event-driven, message queue, pub/sub, Kafka, RabbitMQ, event bus, async messaging, dead letter queue. NOT for: CQRS projections (use cqrs-event-sourcing-architect), real-time WebSocket (use websocket-realtime-expert), observability (use observability-apm-expert).
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Configure gRPC, RabbitMQ, and monorepo contract patterns for NestJS microservices. Use when setting up gRPC service-to-service calls, RabbitMQ event-driven messaging, shared contract libraries, or microservice exception handling in NestJS.
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Use when building data pipelines, ETL jobs, event processors, message-broker producers/consumers, application caching layers, database migrations, BigQuery queries, or event-sourcing handlers in TypeScript. Triggers on edits to indexer/ETL/migration code, Prisma or Drizzle schemas, BigQuery integration code, RabbitMQ/Kafka/SQS/BullMQ producer or consumer code, Redis cache wrappers, or mentions of "data engineering", "ETL", "pipeline", "indexer", "event sourcing", "data warehouse", "data migration", "message queue", "RabbitMQ", "Kafka", "SQS", "BullMQ", "Redis cache", or "caching".
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Develop and refactor Quarkus 3.x LTS services by writing tests first. Covers API responses, event handling, and asynchronous operations, with unit and integration tests plus coverage checks to show how much code is tested.
Build a central platform for collecting, analyzing, and sharing cyber threat information. Connect MISP, OpenCTI, TheHive, and Cortex to import feeds, add context to suspicious indicators, manage cases, and track platform activity.
Create ADRs, short records of architectural decisions, that explain what was chosen, why, and with what trade-offs. Choose among three formats and organize dates, status, numbering, and related links for future team members.
Find the relevant architectural guidance for API design, security, cloud infrastructure, message queues, and caching. This skill acts as an index to specialized references and lists principles for structuring software, distributed systems, and access controls.
Update application code so a developer’s mirrord session identifier travels across service calls, queues, and storage events. Reuse existing tracing tools where possible, then report which request flows carry the identifier and where it still disappears.
Message queue patterns with BullMQ, Kafka, RabbitMQ - saga, outbox, dead letter queue, exactly-once semantics.
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Async communication patterns using message brokers and task queues. Use when building event-driven systems, background job processing, or service decoupling. Covers Kafka (event streaming), RabbitMQ (complex routing), NATS (cloud-native), Redis Streams, Celery (Python), BullMQ (TypeScript), Temporal (workflows), and event sourcing patterns.
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Provides distributed transaction patterns using the Saga Pattern for Spring Boot microservices. Use when implementing distributed transactions across services, handling compensating transactions, ensuring eventual consistency, or building choreography or orchestration-based sagas with Kafka, RabbitMQ, or Axon Framework.
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Use when implementing Kafka, RabbitMQ, Pulsar, or JMS producers and consumers in Spring Boot 4. Covers modular starters, event contracts, idempotency, retries, dead letters, and outbox delivery.
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Use when implementing Kafka, RabbitMQ, Pulsar, or JMS producers and consumers in Spring Boot 3. Covers event contracts, idempotency, retries, dead-letter handling, ordering, and outbox delivery.
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Use when an "enable observability" card asks for queues, or a worker's queue.backlog / consumer lag signals are unbound - which exporter or direct broker data source reads Kafka, RabbitMQ, NATS and Redis queues, the metric names the recipes expect, and the consumer-side metrics the developer adds
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Generates event-driven architecture documentation from AsyncAPI 3.0 specifications. Uses the AsyncAPI parser-js library to extract channels, message schemas, and server bindings for Kafka and RabbitMQ.
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实现异步任务 / 消息队列 / 定时任务 / 后台 worker 时使用。覆盖 RabbitMQ / Kafka / Redis Streams / Bull / Celery / Sidekiq / Spring @Async / Temporal。融合 At-least-once + 幂等 + 死信 + Outbox 模式。
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GraphQL, WebSockets, and microservices patterns for NestJS. Apply only when the relevant package is in dependencies (`@nestjs/graphql`, `@nestjs/websockets`, `@nestjs/microservices`). Each section is orientation, not exhaustive — defer to NestJS docs for deep dives. Use this skill to: - Wire a GraphQL resolver (code-first) with class-validator inputs. - Build a WebSocket gateway with auth and room management. - Set up a microservice transport (TCP/RabbitMQ/NATS/Redis/Kafka) and message handlers. Do NOT use this skill for: - REST controllers (see nest-conventions + decorator-patterns). - ORM (see nest-data-layer). - Auth strategies (see security-analyst phase guidance).
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Use when running background tasks with Celery - worker and broker configuration (Redis, RabbitMQ), task routing by name vs queue, chains/groups/chords, retry patterns (autoretry_for, retry_backoff), acks_late semantics, failure detection, and monitoring with Flower
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Provides distributed transaction patterns using the Saga Pattern for Spring Boot microservices. Use when implementing distributed transactions across services, handling compensating transactions, ensuring eventual consistency, or building choreography or orchestration-based sagas with Kafka, RabbitMQ, or Axon Framework.
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