profile-and-optimize

profile-and-optimize is a Runtime diagnostics & profiling skill for AI agents, published by nygenome in the Lancet2 repository on GitHub. Skillspace rates profile-and-optimize C (72/100) and it passed the safety scan; the rating is based on static analysis only.

Use when investigating Lancet2 performance — slow runs, hot functions, regressions, or candidate optimizations — OR when figuring out how to write, run, or interpret a microbenchmark or CPU profile. Trigger on "profile", "optimize", "slow", "hotspot", "performance", "wall-clock", "benchmark", "DoNotOptimize", "ClobberMemory", "BENCHMARK_F", "benchmark filter", "benchmark variance", "interpret this profile", "what does pprof show", "pprof focus", "analyze_profile", "compare profiles". Builds the profiling tree, runs against real data, analyzes via the project's `analyze_profile.py` (a pprof wrapper), optionally delegates to the perf-analyst subagent, validates each change with both pipeline wall-clock and the google/benchmark microbenchmark suite under `benchmarks/`. The procedural detail — google/benchmark idioms, bench-binary invocation, gperftools internals, pprof and the analyze_profile.py wrapper — lives in `references/` files loaded on demand. The SKILL is the trigger and the…

Grade

C

Quality

72 / 100

Safety

Passed

GitHub stars

29

Unproven: rated by static analysis only, not yet compared head-to-head.

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