Does it support automated performance testing?

Yes, it includes templates for C# xUnit performance tests and PowerShell benchmarking scripts to detect regressions in CI/CD.

How does it improve Whisper AI speed?

It implements optimized command-line flags such as flash attention and entropy thresholds to reduce processing time by up to 70%.

What specific metrics does this skill monitor?

It tracks strict targets including idle RAM (<100MB), active RAM (<300MB), idle CPU (<5%), and transcription latency (<200ms).

Can it help find memory leaks in C#?

Yes, it provides specific dotMemory workflows for identifying growing byte arrays in audio buffers and undisposed event handlers.

VoiceLite Performance Analyzer

Name: VoiceLite Performance Analyzer
Author: mikha08-rgb

bymikha08-rgb

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Analytics & Monitoring

Monitors and optimizes VoiceLite application performance, ensuring adherence to strict RAM, CPU, and transcription latency targets.

About

The Performance Analyzer skill is a specialized tool for Claude Code designed to maintain the lightweight, high-performance nature of the VoiceLite voice-typing application. It provides technical guidance for auditing resource usage, detecting memory leaks in C# audio buffers, and optimizing Whisper AI transcription speeds. By enforcing non-negotiable performance targets—such as keeping idle RAM below 100MB—it empowers developers to profile CPU hotspots with PerfView, analyze memory snapshots with dotMemory, and automate performance regression testing to ensure a seamless, low-latency offline voice-typing experience.

Key Features

Automated performance regression test generation for CI/CD pipelines
Specialized memory leak detection for C# audio buffers and Whisper processes
CPU hotspot analysis and bottleneck identification using PerfView
Automated performance target validation for RAM, CPU, and latency
Whisper AI transcription optimization with sub-800ms processing targets
6 GitHub stars

Use Cases

Debugging UI thread blocking to ensure responsive application behavior during recording
Identifying and fixing 'zombie' Whisper.exe processes that linger after transcription
Optimizing transcription speed using specific command-line flags and quantization

About

Key Features

Automated performance regression test generation for CI/CD pipelines
Specialized memory leak detection for C# audio buffers and Whisper processes
CPU hotspot analysis and bottleneck identification using PerfView
Automated performance target validation for RAM, CPU, and latency
Whisper AI transcription optimization with sub-800ms processing targets
6 GitHub stars

Use Cases

Debugging UI thread blocking to ensure responsive application behavior during recording
Identifying and fixing 'zombie' Whisper.exe processes that linger after transcription
Optimizing transcription speed using specific command-line flags and quantization