AGENT SKILL

sf-testing

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 许可
MIT
最近更新
2026-07-18
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01 前言 Front Matter

name
sf-testing
license
MIT
metadata
{ "author": "Jag Valaiyapathy", "scoring": "120 points across 6 categories", "version": "1.1.0" }
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).

02 资源文件 1

03 SKILL.md 正文

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:


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

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

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

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>

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

Reference Map

Start here

Specialized guidance


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

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