What is the primary purpose of the memtrace skill?

It is used to identify where an OCaml program is allocating memory, specifically focusing on finding 'hotspots' like boxed integers or closures that cause excessive garbage collection pressure.

Can it help optimize Alcotest suites?

Yes, the skill provides specific patterns for instrumenting Alcotest, allowing you to run tracing on specific test cases to isolate allocations.

Does this skill help with performance timing?

No, memtrace is a statistical allocation profiler. For measuring execution time, you should use benchmarks or tools like Sys.time.

Will instrumenting my code with memtrace slow it down permanently?

No, the skill implements tracing gated behind the MEMTRACE environment variable, meaning it only impacts performance when you are actively capturing a trace.

Memtrace Allocation Profiler

Name: Memtrace Allocation Profiler
Author: avsm

byavsm

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Analytics & Monitoring

Profiles and optimizes OCaml memory allocations to eliminate boxing overhead and improve application performance.

About

This skill empowers Claude to perform deep memory profiling for OCaml applications using the memtrace tool. It enables automated instrumentation of executables, capture of statistical traces, and identification of critical allocation hotspots such as unnecessary int32/int64 boxing or closure creation in hot loops. By providing actionable insights and concrete code transformation patterns, it helps developers significantly reduce memory footprint and garbage collection overhead in performance-sensitive OCaml projects.

Key Features

Identification of allocation hotspots and boxing overhead for int32/int64
Analysis of statistical traces to find functions responsible for high memory churn
Concrete optimization patterns for closures and numeric types
Validation of memory improvements via before-and-after trace comparisons
Automated instrumentation of OCaml binaries and Alcotest suites
13 GitHub stars

Use Cases

Isolating memory-heavy code paths within specific unit tests or benchmarks
Optimizing numeric code by identifying and removing redundant boxed integer allocations
Reducing garbage collection pressure in high-throughput parsing or serialization logic

About

Key Features

Identification of allocation hotspots and boxing overhead for int32/int64
Analysis of statistical traces to find functions responsible for high memory churn
Concrete optimization patterns for closures and numeric types
Validation of memory improvements via before-and-after trace comparisons
Automated instrumentation of OCaml binaries and Alcotest suites
13 GitHub stars

Use Cases

Isolating memory-heavy code paths within specific unit tests or benchmarks
Optimizing numeric code by identifying and removing redundant boxed integer allocations
Reducing garbage collection pressure in high-throughput parsing or serialization logic