perf-benchmarker

Run sequential performance benchmarks with strict duration and warmup rules.

951|110|Updated Jan 15, 2026
One-click install
npx skills add https://github.com/agent-sh/agentsys --skill perf-benchmarker-agent-sh
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: perf-benchmarker
Source: https://github.com/agent-sh/agentsys/tree/main/.kiro/skills/perf-benchmarker
Command: npx skills add https://github.com/agent-sh/agentsys --skill perf-benchmarker-agent-sh

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Run sequential benchmarks with strict duration rules to prevent flaky results and ensure reproducible performance measurements.

Core Features & Use Cases

  • Sequential benchmarks guarantee no parallel runs, ensuring determinism.
  • Enforces minimum durations (60s per run, 30s for binary search) and includes a warmup period.
  • Supports anomaly re-runs and a clear output contract with JSON metrics.

Quick Start

Run perf-benchmarker against a target command with a specified duration to measure sequential performance.

Frequently Asked Questions about perf-benchmarker

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

FAQPage Schema
How do I run sequential benchmarks to prevent flaky performance results?

Sequential benchmarks prevent flaky results by guaranteeing no parallel runs and enforcing determinism. This approach applies a 10s warmup and enforces a 60s minimum duration per run to ensure reproducible performance measurements.

What is the minimum duration required for a sequential performance benchmark?

The minimum duration for a sequential performance benchmark is 60s per run, though binary search benchmarks require 30s. A 10s warmup period is also enforced prior to measurement to stabilize execution.

How do I establish baselines and validate performance regressions consistently?

To establish baselines and validate regressions consistently, run sequential benchmarks with strict duration rules. This prevents parallel interference and outputs a JSON metrics block for reliable cross-run comparisons.

How are performance metrics outputted for automated parsing?

Performance metrics are outputted as a JSON block enclosed between PERF_METRICS_START and PERF_METRICS_END markers. This clear output contract allows automated systems to easily extract and parse the sequential benchmark results.

Does the benchmarker handle anomaly re-runs during sequential testing?

Yes, the sequential benchmarker supports anomaly re-runs during testing. Combined with enforced minimum durations and warmup periods, this feature helps validate unexpected results and ensures measurement consistency.