BeClaude

criterium

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1.2kCommunity RegistryDevelopmentby Criterium Team · EPL-1.0

Benchmarking library for Clojure

First seen 5/22/2026

Summary

Criterium is a benchmarking library for Clojure that provides statistically rigorous performance measurements.

  • It helps developers accurately measure execution time, detect performance regressions, and optimize code by accounting for JVM warm-up, garbage collection, and other runtime effects.

Install & Usage

1
Add a marketplace
/plugin marketplace add <org/repo>
2
Install the plugin

Add the configuration to /plugin install criterium@<marketplace>

3
Manage with /plugin
/plugin

Use Cases

Measure the execution time of a Clojure function to compare different implementations.
Detect performance regressions after refactoring or adding new features to your codebase.
Benchmark critical code paths to identify optimization opportunities.
Validate that performance-sensitive functions meet latency requirements.
Compare the performance of alternative data structures or algorithms.
Generate reliable performance reports for continuous integration pipelines.

Usage Examples

1

/criterium (fn [x] (* x x))

2

Benchmark the function (reduce + (range 1000)) with Criterium and report mean execution time.

3

/criterium (sort (shuffle (range 10000)))

View source on GitHub

Security Audits

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Frequently Asked Questions

What is criterium?

Criterium is a benchmarking library for Clojure that provides statistically rigorous performance measurements. It helps developers accurately measure execution time, detect performance regressions, and optimize code by accounting for JVM warm-up, garbage collection, and other runtime effects.

How to install criterium?

To install criterium: add a marketplace (/plugin marketplace add <org/repo>), then add the config to /plugin install criterium@<marketplace>. Finally, /plugin in Claude Code.

What is criterium best for?

criterium is a plugin categorized under Development. Created by Criterium Team.

What can I use criterium for?

criterium is useful for: Measure the execution time of a Clojure function to compare different implementations.; Detect performance regressions after refactoring or adding new features to your codebase.; Benchmark critical code paths to identify optimization opportunities.; Validate that performance-sensitive functions meet latency requirements.; Compare the performance of alternative data structures or algorithms.; Generate reliable performance reports for continuous integration pipelines..