Profile code to identify runtime performance bottlenecks and ranked hotspots.
npx skills add https://github.com/harleypig/dotfiles --skill perf-review-harleypig
Please help me install this Agent Skill. Skill: perf-review Source: https://github.com/harleypig/dotfiles/tree/main/config/claude/skills/perf-review Command: npx skills add https://github.com/harleypig/dotfiles --skill perf-review-harleypig
Identify runtime performance bottlenecks by profiling code and surfacing hotspots for targeted optimization.
Run a baseline profiler on the target codebase and report the top hotspots ranked by measured impact.
High-intent search queries and answers about installing and using this skill.
You identify runtime performance bottlenecks by profiling code against a baseline to surface hotspots. This measure-first workflow delegates profiling to a subagent and outputs ranked, actionable findings for targeted optimization.
The best way to profile code and find slow paths is using a measure-first workflow that separates confirmed findings from hypotheses. It establishes a baseline, reveals the hottest paths, and detects quantifiable slowdowns across services.
Yes, this profiling approach is scalable and applies across multi-service architectures. It effectively detects memory usage and I/O hotspots across libraries and endpoints, handling codebases of varying size and complexity.
Baseline-based profiling reveals memory usage and I/O hotspots by comparing current runtime metrics against an established baseline. This method isolates the hottest paths and quantifiable slowdowns, separating confirmed findings from hypotheses.
Yes, you must establish a baseline before profiling code for hotspots. The workflow requires a baseline measurement to accurately detect slow paths and quantify slowdowns, ensuring findings are ranked by measured impact.
A limitation of this measure-first code analysis is that it separates confirmed findings from hypotheses, meaning speculative optimizations are deprioritized until runtime profiling data validates the quantifiable slowdowns.
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