Skill UI

This skill generates comprehensive TestNG tests in Java, supporting groups, data providers, parallel execution, and XML suite configuration. It helps users create robust test suites with listeners, soft assertions, and lifecycle annotations. Ideal for Java projects requiring automated testing, CI/CD integration, and scalable test execution strategies.

Deploy and manage vLLM for high-throughput LLM inference. Configure continuous batching, tensor parallelism, quantization, and OpenAI-compatible API endpoints for production LLM serving.

Workflow automation ensures AI agents and business processes remain reliable despite failures. This skill covers durable execution patterns and platforms like n8n, Temporal, and Inngest. It transforms brittle scripts into production-grade systems handling sequential, parallel, and orchestrator-worker patterns for payment flows, document analysis, and background jobs.

Ten rules that keep coding agents from re-sending bloated context on every call: locate before reading, compute instead of dumping data, bound noisy command output, never re-read, batch parallel calls and answer lean. Cuts token cost ~32% with unchanged pass rates.

Process many files at once with shared config, bounded parallelism, per-file overrides, and error recovery. Covers the batch command, --file-configs, --max-concurrent, and output layout.