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Found 326 Skills
End-to-end Radius Network development playbook. Stablecoin-native EVM with sub-second finality and 2.8M+ TPS. Uses plain viem (defineChain, createPublicClient, createWalletClient) for all TypeScript integration. wagmi for React wallet integration. Foundry for smart contract development and testing. Covers micropayment patterns (pay-per-visit content, real-time API metering, streaming payments), x402 protocol integration, stablecoin-native fees via Turnstile, ERC-20 operations, event watching, production gotchas, and EVM compatibility differences from Ethereum.
RabbitMQ message broker with AMQP protocol. Covers exchanges, queues, bindings, and messaging patterns. Use for reliable message delivery and complex routing scenarios. USE WHEN: user mentions "rabbitmq", "amqp", "exchanges", "routing patterns", "topic exchange", "fanout", asks about "message routing", "work queues", "request/reply", "flexible routing" DO NOT USE FOR: high-throughput streaming - use `kafka` or `pulsar`; cloud-native - use `nats`; AWS-native - use `sqs`; JMS required - use `activemq`; simple pub/sub - use `redis-pubsub`
Amazon SQS managed message queue service. Covers standard and FIFO queues, dead-letter queues, and integration patterns. Use for AWS-native serverless and microservices architectures. USE WHEN: user mentions "sqs", "aws queues", "fifo queue", "lambda trigger", "sns to sqs", asks about "aws messaging", "serverless queues", "standard queue", "visibility timeout" DO NOT USE FOR: event streaming - use `kafka` or AWS Kinesis; Azure-native - use `azure-service-bus`; GCP-native - use `google-pubsub`; on-premise - use `rabbitmq` or `activemq`; complex routing - use `rabbitmq`
Transcribe audio to text using Sarvam AI's Saaras model. Handles speech recognition, transcription, and voice interfaces for 23 Indian languages. Supports 5 output modes, auto language detection, WebSocket streaming, and batch diarization. Use when converting speech to text or building voice-enabled apps.
Use this skill when working with World Partition, level streaming, level travel, OpenLevel, ServerTravel, data layer, world subsystem, level instance, sub-level, seamless travel, open world, or HLOD. See references/streaming-patterns.md for configuration patterns by game type.
Capture webcam frames and video clips using the aeyes daemon. Use when asked to take a photo, snap a picture, grab a frame, record video, view live webcam stream, or inspect webcam feed. Supports multiple cameras and live streaming via web UI.
Expert guidance for building production-grade AI agents and workflows using Pydantic AI (the `pydantic_ai` Python library). Use this skill whenever the user is: writing, debugging, or reviewing any Pydantic AI code; asking how to build AI agents in Python with Pydantic; asking about Agent, RunContext, tools, dependencies, structured outputs, streaming, multi-agent patterns, MCP integration, or testing with Pydantic AI; or migrating from LangChain/LlamaIndex to Pydantic AI. Trigger even for vague requests like "help me build an AI agent in Python" or "how do I add tools to my LLM app" — Pydantic AI is very likely what they need.
Use this skill when building data pipelines, ETL/ELT workflows, or data transformation layers. Triggers on Airflow DAG design, dbt model creation, Spark job optimization, streaming vs batch architecture decisions, data ingestion, data quality checks, pipeline orchestration, incremental loads, CDC (change data capture), schema evolution, and data warehouse modeling. Acts as a senior data engineer advisor for building reliable, scalable data infrastructure.
FFmpeg-based 4-step video creation: Validate, Prepare, Encode, Verify. Use when user wants to combine a static image with audio to create an MP4 video, create a music video from cover art, or produce podcast/YouTube video from an image and audio file. Use for "image to video", "static video", "mp4 from image", "album art video", or "audio visualization". Do NOT use for video editing, live streaming, or generating images.
AI Elements component library guidance — pre-built React components for AI interfaces built on shadcn/ui. Use when building chat UIs, message displays, tool call rendering, streaming responses, reasoning panels, or any AI-native interface with the AI SDK.
Manages iOS Simulator devices and tests app behavior using xcrun simctl. Covers device lifecycle (create, boot, shutdown, erase, delete), app install and launch, push notification simulation, location simulation, permission grants via privacy subcommand, deep link testing via openurl, status bar overrides, screenshot and video recording, log streaming with os_log filtering, get_app_container paths, and #if targetEnvironment(simulator) compile-time checks. Use when creating or managing simulator devices, testing push notifications without APNs, simulating GPS locations, granting or resetting privacy permissions, capturing screenshots or screen recordings from the command line, streaming device logs, debugging simulator boot failures, troubleshooting CoreSimulator issues, or checking simulator hardware limitations.
Event-driven architecture patterns including message queues, pub/sub, event sourcing, CQRS, and sagas. Use for async messaging, distributed transactions, event stores, domain/integration events, data streaming, choreography/orchestration, or integrating with Kafka, RabbitMQ, Pulsar, SQS/SNS, or NATS.