sf-apex

jaganpro/sf-skills · updated Apr 8, 2026

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$npx skills add https://github.com/jaganpro/sf-skills --skill sf-apex
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summary

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.

skill.md

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:


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

High-signal checklists

Specialized patterns

Troubleshooting / validation


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
how to use sf-apex

How to use sf-apex on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add sf-apex
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/jaganpro/sf-skills --skill sf-apex

The skills CLI fetches sf-apex from GitHub repository jaganpro/sf-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/sf-apex

Reload or restart Cursor to activate sf-apex. Access the skill through slash commands (e.g., /sf-apex) or your agent's skill management interface.

Security & Verification 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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.775 reviews
  • Kwame Thomas· Dec 28, 2024

    Keeps context tight: sf-apex is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Min Gupta· Dec 24, 2024

    sf-apex is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Noor Smith· Dec 8, 2024

    We added sf-apex from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Min Farah· Dec 8, 2024

    Solid pick for teams standardizing on skills: sf-apex is focused, and the summary matches what you get after install.

  • Min Nasser· Dec 8, 2024

    sf-apex fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Noor Taylor· Dec 4, 2024

    Useful defaults in sf-apex — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Lucas White· Dec 4, 2024

    We added sf-apex from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Neel Rahman· Nov 27, 2024

    sf-apex has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Mateo Robinson· Nov 27, 2024

    I recommend sf-apex for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Ren Desai· Nov 23, 2024

    sf-apex is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

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