performance-analysis

Analyze benchmark result JSON to detect slow transforms, warmup instability, and regressions.

95|3|Updated Oct 25, 2024

Search Tags:#performance #optimization #profiling #benchmark #analyze #results

Ready to run

npx skills add https://github.com/albumentations-team/benchmark --skill performance-analysis-albumentations-team

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: performance-analysis
Source: https://github.com/albumentations-team/benchmark/tree/main/.cursor/skills/performance-analysis
Command: npx skills add https://github.com/albumentations-team/benchmark --skill performance-analysis-albumentations-team

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyzes benchmark results to identify slow transforms, warmup issues, and performance regressions. Compares speedups across libraries and generates optimization recommendations. Use when analyzing performance, investigating slow benchmarks, or comparing library results.

Core Features & Use Cases

Analyze results to detect bottlenecks, slow transforms, and stability issues across library backends.
Compare speedups and surface actionable optimization recommendations to guide profiling and tuning.
Use in performance review workflows to validate improvements and catch regressions.

Quick Start

Run this skill on the latest benchmark results to surface bottlenecks and generate optimization recommendations.

Frequently Asked Questions about performance-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I analyze benchmark results to find slow transforms?▼

To analyze benchmark results, the skill parses metrics like median throughput from JSON output to surface slow transforms and generate optimization recommendations for profiling and tuning.

What causes warmup instability during performance profiling?▼

Warmup instability during performance profiling is identified by parsing warmup iteration metrics within benchmark results to detect fluctuations and surface stability issues across library backends.

Can I compare speedups across different libraries using benchmark JSON?▼

Yes, you can compare speedups across libraries by analyzing benchmark JSON output to evaluate relative performance, validate improvements, and catch regressions in your review workflow.

How do I detect performance regressions in post-run analysis?▼

To detect performance regressions in post-run analysis, the skill reads library_results.json, evaluates median throughput trends, and outputs diagnostic insights highlighting degraded transform speeds.

Does this performance analysis require specific JSON input formats?▼

Yes, performance analysis requires benchmark JSON input, specifically reading from output/library_results.json to parse median throughput and warmup iterations for diagnostic insights.