performance

Installation
SKILL.md

Performance Optimization

Performance work follows one rule above all others: measure before you change anything. Intuition about bottlenecks is wrong more often than it is right. Every optimization should start with profiling, produce a hypothesis, apply a targeted fix, and verify with another measurement.

Core Principles

Principle Meaning
Measure first Never optimize without profiling data -- gut feelings about bottlenecks are unreliable
Optimize the critical path Focus on the code that runs most frequently or blocks user-visible latency
Set budgets Define acceptable latency, throughput, and resource usage before you start
Avoid premature optimization Readable, correct code first -- optimize only when measurements show a real problem
Know your tradeoffs Every optimization trades something (memory for speed, complexity for throughput, freshness for latency)

Profiling and Benchmarking

Profiling identifies where time and resources are spent. Without it, you are guessing.

Installs
34
GitHub Stars
19
First Seen
Mar 7, 2026
performance — krzysztofsurdy/code-virtuoso