Can it help me improve my code coverage?

Absolutely. It provides tools to generate coverage profiles and identify untested code paths to help you reach your coverage targets.

Does this skill support the latest Go testing features?

Yes, it includes support for modern Go testing capabilities such as native fuzzing and parallel subtests introduced in recent versions of Go.

How does it handle performance testing?

It implements Go's benchmark package patterns, including timer resets, allocation reporting, and parallel benchmarking for multi-core performance analysis.

Which mocking libraries are compatible with this skill?

The skill provides specific patterns for Testify and GoMock, but the general mocking strategies can be adapted to any interface-based mocking library.

Go Testing Mastery

Name: Go Testing Mastery
Author: pluginagentmarketplace

bypluginagentmarketplace

•

Security & Testing

Implements comprehensive Go testing strategies including table-driven tests, mocking, and performance benchmarks to ensure high-quality code.

About

The Go Testing Mastery skill equips Claude with specialized knowledge to architect robust test suites for Go applications. It provides standardized patterns for creating table-driven tests, implementing interface mocks using popular libraries like Testify, and conducting performance benchmarks. This skill is particularly useful for developers looking to achieve high code coverage, detect race conditions in concurrent code, and utilize modern Go features like native fuzzing to uncover edge-case vulnerabilities.

Key Features

Performance benchmarking and parallel execution strategies
Integrated native Go fuzzing for edge-case detection
Automated generation of table-driven test structures
Race condition detection and code coverage optimization
Comprehensive mocking patterns for interfaces and external services
3 GitHub stars

Use Cases

Securing data parsers and input logic through automated fuzzing
Building resilient test suites for high-concurrency Go microservices
Profiling and optimizing hot paths in Go applications via benchmarks

About

Key Features

Performance benchmarking and parallel execution strategies
Integrated native Go fuzzing for edge-case detection
Automated generation of table-driven test structures
Race condition detection and code coverage optimization
Comprehensive mocking patterns for interfaces and external services
3 GitHub stars

Use Cases

Securing data parsers and input logic through automated fuzzing
Building resilient test suites for high-concurrency Go microservices
Profiling and optimizing hot paths in Go applications via benchmarks