When should I avoid using this performance skill?

You should avoid using these timing wrappers in extremely high-frequency 'hot paths' where the overhead of the measurement itself could significantly impact performance, or for single operations that are too fast to measure meaningfully.

Can this skill help with progress reporting in batch jobs?

Yes, it is designed to handle multiple inputs, providing real-time statistics on success rates and processing speeds (items per second) as tasks complete.

Why does this skill use process_time instead of wall-clock time?

Process_time specifically measures the time the CPU spends on the current process, making it much more stable and reliable for benchmarking than wall-clock time, which can be affected by system background tasks.

What kind of statistics does the Time and Report skill provide?

It typically reports the total count of operations, average time per operation, maximum time taken, and the overall frequency or throughput (Hz).

Performance Profiling & Reporting

Name: Performance Profiling & Reporting
Author: jimmc414

byjimmc414

•

Analytics & Monitoring

Benchmarks code execution using CPU process timing to generate detailed performance summaries and throughput statistics.

The Time and Report skill enables Claude to implement professional-grade performance monitoring patterns inspired by Peter Norvig's programming style. It focuses on using CPU process time for stable measurements, calculating throughput rates (Hz), and generating statistical summaries including average and maximum execution times. This skill is ideal for developers optimizing algorithms, comparing multiple implementations, or requiring real-time progress reporting for batch processing tasks where accuracy and meaningful units (like puzzles per second) are essential.

Key Features

01Integrated success rate tracking to monitor accuracy alongside speed

02Customizable reporting units for domain-specific benchmarking

03Automated throughput calculations and frequency reporting in Hz

041 GitHub stars

05Comprehensive statistical summaries including average, max, and total execution times

06CPU-based timing decorators for stable, non-blocking performance measurement

Use Cases

01Comparing the computational efficiency of different algorithm implementations

02Monitoring throughput and progress during large-scale data processing tasks

03Benchmarking performance-critical applications like solvers, parsers, or ML pipelines

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jimmc414/claude-code-plugin-marketplace time-and-report

For use in Claude.ai and ChatGPT

Download Skill