Skill UI

This skill monitors the performance of Claude Code and your local system environment. It diagnoses slowness, measures CPU, RAM, and disk usage, checks API latency, and generates system health reports. It helps identify bottlenecks like high CPU usage, memory pressure, or network latency affecting your coding workflow.

Implement distributed tracing with Jaeger and Tempo for request flow visibility across microservices. Configure OpenTelemetry SDK and exporters to diagnose latency and errors. Ensure secure context propagation without logging sensitive data. Verify trace spans and sampling strategies for production observability.

Build real-time bidirectional streaming applications using the Gemini Live API. Supports WebSocket-based audio/video/text streaming, voice activity detection, function calling, and session management. Includes SDKs for Python and JavaScript for low-latency AI interactions.

Diagnoses data pipeline performance issues such as slow jobs, expensive queries, and latency trends using Monte Carlo's cross-platform observability. Works across Airflow, dbt, Databricks, and warehouse query engines to find bottlenecks, detect regressions, and identify root causes.

This blueprint guides the creation of F.R.I.D.A.Y., a tactical, low-latency voice assistant inspired by Iron Man. It utilizes the specialized Pipecat framework to orchestrate a comprehensive, real-time audio pipeline: STT (OpenAI Whisper/GPT-4o) -> LLM (Gemini) -> TTS (OpenAI Nova). Ideal for developers needing to build advanced, multi-provider, conversational voice applications.

RouterBase acts as a unified, OpenAI-compatible API gateway, allowing applications to route requests across diverse large language models (LLMs) like GPT, Claude, and Gemini. It helps developers migrate existing OpenAI SDK calls, implement sophisticated primary/fallback model selection based on cost, latency, and quality, and manage multimodal payloads (image, audio, video) from a single, standardized endpoint.

Voice agents enable natural human-AI conversation through speech recognition and synthesis. This skill covers low-latency architectures like speech-to-speech pipelines and STT-LLM-TTS workflows. It includes optimization strategies for sub-800ms response times, voice activity detection, and integration with tools like Deepgram, ElevenLabs, and OpenAI. Ideal for building production-ready voice assistants with natural interaction flows.

Expert in building voice AI applications - from real-time voice agents to voice-enabled apps. Covers OpenAI Realtime API, Vapi, Deepgram, ElevenLabs, LiveKit, and WebRTC. Focuses on low-latency, production-ready voice experiences.

This skill diagnoses latency and throughput in weather data workflows by measuring stages like discovery, transfer, parsing, and rendering separately. It identifies bottlenecks before code changes, supporting profiling and validation of performance fixes. It ensures accurate optimization by isolating slow steps in the pipeline.