---name: sf-apexdescription: >TRIGGER when: user writes, reviews, or fixes Apex classes, triggers, test classes,DO NOT TRIGGER when: LWC JavaScript (use sf-lwc), Flow XML (use sf-flow),license: MITmetadata: version: 1.1.0author: Jag Valaiyapathyscoring: 150 points across 8 categories---

sf-apex: Salesforce Apex Code Generation and Review

Use this skill when the user needs production Apex: new classes, triggers, selectors, services, async jobs, invocable methods, test classes, or evidence-based review of existing .cls / .trigger code.

When This Skill Owns the Task

Use sf-apex when the work involves:

• Apex class generation or refactoring
• trigger design and trigger-framework decisions
• @InvocableMethod, Queueable, Batch, Schedulable, or test-class work
• review of bulkification, sharing, security, testing, or maintainability

Delegate elsewhere when the user is:

• editing LWC JavaScript / HTML / CSS → sf-lwc
• building Flow XML or Flow orchestration → sf-flow
• writing SOQL only → sf-soql
• deploying or validating metadata to orgs → sf-deploy

---

Required Context to Gather First

Ask for or infer:

• class type: trigger, service, selector, batch, queueable, schedulable, invocable, test
• target object(s) and business goal
• whether code is net-new, refactor, or fix
• org / API constraints if known
• expected test coverage or deployment target

Before authoring, inspect the project shape:

• existing classes / triggers
• current trigger framework or handler pattern
• related tests, flows, and selectors
• whether TAF is already in use

---

Recommended Workflow

1. Discover local architecture

Check for:

• existing trigger handlers / frameworks
• service-selector-domain conventions
• related tests and data factories
• invocable or async patterns already used in the repo

2. Choose the smallest correct pattern

Need	Preferred pattern
simple reusable logic	service class
query-heavy data access	selector
single object trigger behavior	one trigger + handler / TAF action
Flow needs complex logic	@InvocableMethod
background processing	Queueable by default
very large datasets	Batch Apex or Database.Cursor patterns
repeatable verification	dedicated test class + test data factory

3. Author with guardrails

Generate code that is:

• bulk-safe
• sharing-aware
• CRUD/FLS-safe where applicable
• testable in isolation
• consistent with project naming and layering

4. Validate and score

Evaluate against the 150-point rubric before handoff.

5. Hand off deploy/test next steps

When org validation is needed, hand off to:

• sf-testing for test execution loops
• sf-deploy for deploy / dry-run / verification

---

Generation Guardrails

Never generate these without explicitly stopping and explaining the problem:

Anti-pattern	Why it blocks
SOQL in loops	governor-limit failure
DML in loops	governor-limit failure
missing sharing model	security / data exposure risk
hardcoded IDs	deployment and portability failure
empty catch blocks	silent failure / poor observability
string-built SOQL with user input	injection risk
tests without assertions	false-positive test suite

Default fix direction:

• query once, operate on collections
• use with sharing unless justified otherwise
• use bind variables and WITH USER_MODE where appropriate
• create assertions for positive, negative, and bulk cases

See references/anti-patterns.md and references/security-guide.md.

---

High-Signal Build Rules

Trigger architecture

• Prefer one trigger per object.
• If TAF is already installed and used, extend it instead of inventing a second trigger pattern.
• Triggers should delegate logic; avoid heavy business logic directly in trigger bodies.

Async choice

Scenario	Default
standard async work	Queueable
very large record processing	Batch Apex
recurring schedule	Scheduled Flow or Schedulable
post-job cleanup	Finalizer
long-running Lightning callouts	Continuation

Testing minimums

Use the PNB pattern for every feature:

• Positive path
• Negative / error path
• Bulk path (251+ records where relevant)

Modern Apex expectations

Prefer current idioms when available:

• safe navigation: obj?.Field__c
• null coalescing: value ?? fallback
• Assert.* over legacy assertion style
• WITH USER_MODE and explicit security handling where relevant

---

Output Format

When finishing, report in this order:

1. What was created or reviewed
2. Files changed
3. Key design decisions
4. Risk / guardrail notes
5. Test guidance
6. Deployment guidance

Suggested shape:

Apex work: <summary>
Files: <paths>
Design: <pattern / framework choices>
Risks: <security, bulkification, async, dependency notes>
Tests: <what to run / add>
Deploy: <dry-run or next step>

---

LSP Validation Note

This skill supports an LSP-assisted authoring loop for .cls and .trigger files:

• syntax issues can be detected immediately after write/edit
• the skill can auto-fix common syntax errors in a short loop
• semantic quality still depends on the 150-point review rubric

Full guide: references/troubleshooting.md

---

Cross-Skill Integration

Need	Delegate to	Reason
describe objects / fields first	sf-metadata	avoid coding against wrong schema
seed bulk or edge-case data	sf-data	create realistic test datasets
run Apex tests / fix failing tests	sf-testing	execute and iterate on failures
deploy to org	sf-deploy	validation and deployment orchestration
build Flow that calls Apex	sf-flow	declarative orchestration
build LWC that calls Apex	sf-lwc	UI/controller integration

---

Reference Map

Start here

• references/patterns-deep-dive.md
• references/security-guide.md
• references/bulkification-guide.md
• references/testing-patterns.md

High-signal checklists

• references/code-review-checklist.md
• references/anti-patterns.md
• references/naming-conventions.md

Specialized patterns

• references/trigger-actions-framework.md
• references/automation-density-guide.md
• references/flow-integration.md
• references/triangle-pattern.md
• references/design-patterns.md
• references/solid-principles.md

Troubleshooting / validation

• references/troubleshooting.md
• references/llm-anti-patterns.md
• references/testing-guide.md

---

Score Guide

Score	Meaning
120+	strong production-ready Apex
90–119	good implementation, review before deploy
67–89	acceptable but needs improvement
< 67	block deployment