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name: sf-testing description: > Apex test execution, coverage analysis, and test-fix loops with 120-point scoring. TRIGGER when: user runs Apex tests, checks code coverage, fixes failing tests, or touches *Test.cls / *_Test.cls files. DO NOT TRIGGER when: writing Apex production code (use sf-apex), Agentforce agent testing (use sf-ai-agentforce-testing), or Jest/LWC tests (use sf-lwc). license: MIT metadata: version: "1.1.0" author: "Jag Valaiyapathy" scoring: "120 points across 6 categories"

sf-testing: Salesforce Test Execution & Coverage Analysis

Use this skill when the user needs Apex test execution and failure analysis: running tests, checking coverage, interpreting failures, improving coverage, and managing a disciplined test-fix loop for Salesforce code.

When This Skill Owns the Task

Use sf-testing when the work involves:

• sf apex run test workflows
• Apex unit-test failures
• code coverage analysis
• identifying uncovered lines and missing test scenarios
• structured test-fix loops for Apex code

Delegate elsewhere when the user is:

• writing or refactoring production Apex → sf-apex
• testing Agentforce agents → sf-ai-agentforce-testing
• testing LWC with Jest → sf-lwc

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Required Context to Gather First

Ask for or infer:

• target org alias
• desired test scope: single class, specific methods, suite, or local tests
• coverage threshold expectation
• whether the user wants diagnosis only or a test-fix loop
• whether related test data factories already exist

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Recommended Workflow

1. Discover test scope

Identify:

• existing test classes
• target production classes
• test data factories / setup helpers

2. Run the smallest useful test set first

Start narrow when debugging a failure; widen only after the fix is stable.

3. Analyze results

Focus on:

• failing methods
• exception types and stack traces
• uncovered lines / weak coverage areas
• whether failures indicate bad test data, brittle assertions, or broken production logic

4. Run a disciplined fix loop

When the issue is code or test quality:

• delegate code fixes to sf-apex when needed
• add or improve tests
• rerun focused tests before broader regression

5. Improve coverage intentionally

Cover:

• positive path
• negative / exception path
• bulk path (251+ records where appropriate)
• callout or async path when relevant

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High-Signal Rules

• default to SeeAllData=false
• every test should assert meaningful outcomes
• test bulk behavior, not just single-record happy paths
• use factories / @TestSetup when they improve clarity and speed
• pair Test.startTest() with Test.stopTest() when async behavior matters
• do not hide flaky org dependencies inside tests

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Output Format

When finishing, report in this order:

1. What tests were run
2. Pass/fail summary
3. Coverage result
4. Root-cause findings
5. Fix or next-run recommendation

Suggested shape:

Test run: <scope>
Org: <alias>
Result: <passed / partial / failed>
Coverage: <percent / key classes>
Issues: <highest-signal failures>
Next step: <fix class, add test, rerun scope, or widen regression>

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Cross-Skill Integration

| Need | Delegate to | Reason | |---|---|---| | fix production code or author tests | sf-apex | code generation and repair | | create bulk / edge-case data | sf-data | realistic test datasets | | deploy updated tests | sf-deploy | rollout | | inspect detailed runtime logs | sf-debug | deeper failure analysis |

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Reference Map

Start here

• references/cli-commands.md
• references/test-patterns.md
• references/testing-best-practices.md
• references/test-fix-loop.md

Specialized guidance

• references/mocking-patterns.md
• references/performance-optimization.md
• assets/

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Score Guide

| Score | Meaning | |---|---| | 108+ | strong production-grade test confidence | | 96–107 | good test suite with minor gaps | | 84–95 | acceptable but strengthen coverage / assertions | | < 84 | below standard; revise before relying on it |