stream-validator

The stream-validator skill provides an automated diagnostics toolkit for the WaveCap-SDR ecosystem. It is designed for engineers and radio enthusiasts who need to monitor real-time streaming performance, debug connection issues, or verify signal integrity under various load conditions. By interfacing directly with the WaveCap-SDR backend API, this skill allows users to measure throughput, detect buffer underruns, and perform quantitative analysis on incoming audio, spectrum, and IQ data streams. It bridges the gap between raw data transmission and high-level performance metrics, making it essential for infrastructure monitoring, performance tuning, and troubleshooting streaming instability in distributed SDR setups.

• Performs comprehensive health checks on server status, device enumeration, and active capture channels.

• Validates stream performance metrics including connection establishment time, bytes received, and sample continuity for PCM, FFT, and complex IQ data.

• Analyzes signal quality features like RMS levels, peak power detection, silence thresholding, and clipping indicators for audio channels.

• Provides detailed diagnostic output for WebSocket and HTTP stream types, identifying packet gaps, throughput deviations, and latency issues in real-time.

• Automates server health reporting including subscriber counts and zombie process cleanup status.

• Ensure the WaveCap-SDR server is running on the target port (default 8087) before executing validation commands.

• Use the --verbose flag to perform deep audio quality analysis and detect anomalies like signal clipping or unexpected silence.

• Leverage the --report flag to generate machine-readable JSON outputs for integration into CI/CD pipelines or automated infrastructure monitoring dashboards.

• Expected throughput varies significantly by stream type; reference technical documentation for baseline performance targets regarding PCM16, FFT bins, and IQ sample rates.

• Works with common SDR hardware platforms like RTL-SDR and SDRplay, utilizing the Python backend environment to maintain system-level compatibility and accuracy.