Fetches perl-testing from affaan-m/everything-claude-code and configures it for Cursor.
3
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/perl-testing
Restart Cursor to activate perl-testing. Access via /perl-testing in your agent's command palette.
⚠
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 testing strategies for Perl applications using Test2::V0, Test::More, prove, and TDD methodology.
When to Activate
Writing new Perl code (follow TDD: red, green, refactor)
Designing test suites for Perl modules or applications
Reviewing Perl test coverage
Setting up Perl testing infrastructure
Migrating tests from Test::More to Test2::V0
Debugging failing Perl tests
TDD Workflow
Always follow the RED-GREEN-REFACTOR cycle.
# Step 1: RED — Write a failing test# t/unit/calculator.tusev5.36;use Test2::V0;use lib 'lib';use Calculator;subtest 'addition'=>sub{my$calc= Calculator->new; is($calc->add(2,3),5,'adds two numbers'); is($calc->add(-1,1),0,'handles negatives');};done_testing;# Step 2: GREEN — Write minimal implementation# lib/Calculator.pmpackage Calculator;usev5.36;use Moo;subadd($self,$a,$b){return$a+$b;}1;# Step 3: REFACTOR — Improve while tests stay green# Run: prove -lv t/unit/calculator.t
Test::More Fundamentals
The standard Perl testing module — widely used, ships with core.
Basic Assertions
usev5.36;use Test::More;# Plan upfront or use done_testing# plan tests => 5; # Fixed plan (optional)# Equalityis($result,42,'returns correct value');isnt($result,0,'not zero');# Booleanok($user->is_active,'user is active');ok(!$user->is_banned,'user is not banned');# Deep comparisonis_deeply($got,{ name =>'Alice', roles =>['admin']},'returns expected structure');# Pattern matchinglike($error,qr/not found/i,'error mentions not found');unlike($output,qr/password/,'output hides password');# Type checkisa_ok($obj,'MyApp::User');can_ok($obj,'save','delete');done_testing;
SKIP and TODO
usev5.36;use Test::More;# Skip tests conditionallySKIP:{ skip 'No database configured',2unless$ENV{TEST_DB};my$db= connect_db(); ok($db->ping,'database is reachable'); is($db->version,'15','correct PostgreSQL version');}# Mark expected failuresTODO:{local$TODO='Caching not yet implemented'; is($cache->get('key'),'value','cache returns value');}done_testing;
Test2::V0 Modern Framework
Test2::V0 is the modern replacement for Test::More — richer assertions, better diagnostics, and extensible.
Why Test2?
Superior deep comparison with hash/array builders
Better diagnostic output on failures
Subtests with cleaner scoping
Extensible via Test2::Tools::* plugins
Backward-compatible with Test::More tests
Deep Comparison with Builders
usev5.36;use Test2::V0;# Hash builder — check partial structureis($user->to_hash, hash { field name =>'Alice'; field email => match(qr/\@example\.com$/); field age => validator(sub{$_>=18});# Ignore other fields etc();},'user has expected fields');# Array builderis($result, array { item 'first'; item match(qr/^second/); item DNE();# Does Not Exist — verify no extra items},'result matches expected list');# Bag — order-independent comparisonis($tags, bag { item 'perl'; item 'testing'; item 'tdd';},'has all required tags regardless of order');
usev5.36;use Test2::V0;# Test that code dieslike( dies { divide(10
Implementation Guide
Prerequisites
›Claude Desktop or compatible AI client with skill support
›Clear understanding of task or problem to solve
›Willingness 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
⚠Expecting perfect results without iteration
⚠Not providing enough context in prompts
⚠Using skill for tasks outside its intended scope
⚠Accepting outputs without review and validation
Best Practices
✓ 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
✗ Don't
−Don't use without understanding skill limitations
−Don't skip validation of outputs
−Don't share sensitive information in prompts
−Don't expect skill to replace human judgment
💡 Pro Tips
★Be specific about desired format and style
★Ask for multiple options to choose from
★Request explanations to understand reasoning
★Combine AI efficiency with human expertise
When to Use This
✓ 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.
✗ 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
