interpret-benchmarks

Analyzes XCTest benchmark output to assess reliability, scaling behavior, and performance regressions.

1|Updated Apr 5, 2026
One-click install
npx skills add https://github.com/moolah-rocks/moolah-native --skill interpret-benchmarks-moolah-rocks
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: interpret-benchmarks
Source: https://github.com/moolah-rocks/moolah-native/tree/main/.claude/skills/interpret-benchmarks
Command: npx skills add https://github.com/moolah-rocks/moolah-native --skill interpret-benchmarks-moolah-rocks

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Raw benchmark output from just benchmark is hard to act on: numbers without context don't tell you whether a result is trustworthy, whether scaling is acceptable, or whether a regression actually occurred. This Skill provides a structured decision process for reading XCTest performance measurements and deciding what to do next. ## Core Features & Use Cases - Reliability Assessment: Classifies results by relative standard deviation so you know whether a measurement can support a conclusion before comparing numbers. - Scaling Analysis: Computes 1x vs 2x ratios to distinguish constant, linear, super-linear, and quadratic behavior in GRDB database operations. - Anomaly Detection: Interprets per-iteration value arrays to spot outliers, steady growth from database leakage, and bimodal distributions. - Use Case: After a code change, a benchmark fails against its Xcode baseline. Use this Skill to confirm the regression, check stddev validity, then use Instruments with os_signpost to locate the bottleneck before optimizing. ## Quick Start Run just benchmark, save the output, and ask the assistant to interpret the results and recommend next steps.

Frequently Asked Questions about interpret-benchmarks

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

FAQPage Schema
How do I interpret XCTest benchmark results?▼

Extract the average time, relative standard deviation, and per-iteration values for each benchmark. Check stddev first: under 5% is highly reliable, over 20% is unreliable and should not support conclusions. Then compare scaling ratios and baselines before deciding on action.

What standard deviation is acceptable for performance benchmarks?▼

Under 5% stddev is highly reliable and safe for comparing small differences. 5-10% is normal for GRDB database operations, 10-20% only detects large regressions, and above 20% means the benchmark itself needs fixing before any conclusion.

Why are my benchmark results noisy or inconsistent?▼

High variance usually comes from other work running on the machine, setup or teardown leaking into the measure block, an in-memory GRDB database growing across iterations, or autorelease pool buildup. Reset the database between iterations and wrap conversions in autoreleasepool.

How do I detect a performance regression after a code change?▼

Compare the benchmark output against the Xcode baseline; a red failure exceeding baseline plus tolerance indicates a regression. Review git diff for changes in the relevant code path, then confirm with Instruments os_signpost profiling before fixing and re-benchmarking.

What scaling ratio between 1x and 2x datasets indicates a problem?▼

A ratio near 1.0 means constant-time behavior, 1.5-2.2 is acceptable linear scaling, 2.5-4.0 suggests super-linear O(n log n) or worse worth investigating, and above 4.0 indicates quadratic behavior that should be treated as a performance bug.