Reads CPU flame-graph output from py-spy (Python), async-profiler (JVM), Go pprof, or Node.js `perf_hooks` / clinic.js: identifies the hot path (top sample-time frames), classifies the bottleneck (CPU-bound vs lock contention vs allocator pressure), and proposes the next investigation step. Use when a perf regression is bisected to a commit but the hot path inside it is unclear; for tail-latency percentiles use the latency-percentiles reference in k6-load-testing, and for a slow SQL hot path use db-query-plan-analyzer.
72
91%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
View guide
Passed
No findings from the security scan
Tessl evals compare success rates of agents with and without our optimized context