Confirm successful installation by checking the skill directory location:
.cursor/skills/golang-testing
Restart Cursor to activate golang-testing. Access via /golang-testing in your agent's command palette.
โ
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Comprehensive Go testing patterns for writing reliable, maintainable tests following TDD methodology.
When to Activate
Writing new Go functions or methods
Adding test coverage to existing code
Creating benchmarks for performance-critical code
Implementing fuzz tests for input validation
Following TDD workflow in Go projects
TDD Workflow for Go
The RED-GREEN-REFACTOR Cycle
RED โ Write a failing test first
GREEN โ Write minimal code to pass the test
REFACTOR โ Improve code while keeping tests green
REPEAT โ Continue with next requirement
Step-by-Step TDD in Go
// Step 1: Define the interface/signature// calculator.gopackage calculator
funcAdd(a, b int)int{panic("not implemented")// Placeholder}// Step 2: Write failing test (RED)// calculator_test.gopackage calculator
import"testing"funcTestAdd(t *testing.T){ got :=Add(2,3) want :=5if got != want { t.Errorf("Add(2, 3) = %d; want %d", got, want)}}// Step 3: Run test - verify FAIL// $ go test// --- FAIL: TestAdd (0.00s)// panic: not implemented// Step 4: Implement minimal code (GREEN)funcAdd(a, b int)int{return a + b
}// Step 5: Run test - verify PASS// $ go test// PASS// Step 6: Refactor if needed, verify tests still pass
Table-Driven Tests
The standard pattern for Go tests. Enables comprehensive coverage with minimal code.
funcTestAdd(t *testing.T){ tests :=[]struct{ name string a, b int expected int}{{"positive numbers",2,3,5},{"negative numbers",-1,-2,-3},{"zero values",0,0,0},{"mixed signs",-1,1,0},{"large numbers",1000000,2000000,3000000},}for_, tt :=range tests { t.Run(tt.name,func(t *testing.T){ got :=Add(tt.a, tt.b)if got != tt.expected { t.Errorf("Add(%d, %d) = %d; want %d", tt.a, tt.b, got, tt.expected)}})}}
funcTestUser(t *testing.T){// Setup shared by all subtests db :=setupTestDB(t) t.Run("Create",func(t *testing.T){ user :=&User{Name:"Alice"} err := db.CreateUser(user)if err !=nil{ t.Fatalf("CreateUser failed: %v", err)}if user.ID ==""{ t.Error("expected user ID to be set")}}) t.Run("Get",func(t *testing.T){ user, err := db.GetUser("alice-id")if err !=nil
Implementation Guide
Prerequisites
โบClaude Desktop or compatible AI client with skill support
โบClear understanding of task or problem to solve
โบWillingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Steps
1Install skill using provided installation command
2Test with simple use case relevant to your work
3Evaluate output quality and relevance
4Iterate on prompts to improve results
5Integrate into regular workflow if valuable
Common Pitfalls
โ Expecting perfect results without iteration
โ Not providing enough context in prompts
โ Using skill for tasks outside its intended scope
โ Accepting outputs without review and validation
Best Practices
โ Do
+Start with clear, specific prompts
+Provide relevant context and constraints
+Review and refine all outputs before using
+Iterate to improve output quality
+Document successful prompt patterns
โ Don't
โDon't use without understanding skill limitations
โDon't skip validation of outputs
โDon't share sensitive information in prompts
โDon't expect skill to replace human judgment
๐ก Pro Tips
โ Be specific about desired format and style
โ Ask for multiple options to choose from
โ Request explanations to understand reasoning
โ Combine AI efficiency with human expertise
When to Use This
โ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
โ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path
1Familiarize yourself with skill capabilities and limitations
2Start with low-risk, non-critical tasks
3Progress to more complex and valuable use cases
4Build expertise through regular use and experimentation