Experience Lwc Generate logo

Experience Lwc Generate

OrganizationPopular
forcedotcom
experience-lwc-generate

Lightning Web Components with PICKLES methodology and 165-point scoring. Use this skill when the user creates or edits LWC components, builds wire service patterns, or writes Jest tests for LWC. TRIGGER when: user creates/edits LWC components, touches lwc/**/*.js, .html, .css, .js-meta.xml files, or asks about wire service, SLDS, or Jest LWC tests. DO NOT TRIGGER when: Apex classes (use platform-apex-generate), Aura components, or Visualforce.

Overview

Publisherforcedotcom
Repositorysf-skills
Skill nameexperience-lwc-generate
Stars
1.1K
Forks
351
Bundled files
57
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 57 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by forcedotcom on GitHub. Read the source before you install it.

Installation

Install the Experience Lwc Generate AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/forcedotcom/sf-skills/tree/main/plugins/builder/experience-lwc/skills/experience-lwc-generate
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/forcedotcom/sf-skills.git /tmp/sf-skills
mkdir -p .claude/skills
cp -r /tmp/sf-skills/plugins/builder/experience-lwc/skills/experience-lwc-generate .claude/skills/experience-lwc-generate
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Experience Lwc Generate in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Experience Lwc Generate on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Experience Lwc Generate is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

experience-lwc-generate: Lightning Web Components Development

Use this skill when the user needs Lightning Web Components: LWC bundles, wire patterns, Apex/GraphQL integration, SLDS 2 styling, accessibility, performance work, or Jest unit tests.

When This Skill Owns the Task

Use experience-lwc-generate when the work involves:

  • lwc/**/*.js, .html, .css, .js-meta.xml
  • component scaffolding and bundle design
  • wire service, Apex integration, GraphQL integration
  • SLDS 2, dark mode, and accessibility work
  • Jest unit tests for LWC

Delegate elsewhere when the user is:


Required Context to Gather First

Ask for or infer:

  • component purpose and target surface
  • data source: LDS, Apex, GraphQL, LMS, or external system via Apex
  • whether the user needs tests
  • whether the component must run in Flow, App Builder, Experience Cloud, or dashboard contexts
  • accessibility and styling expectations

Recommended Workflow

1. Choose the right architecture

Use the PICKLES mindset:

  • prototype
  • integrate the right data source
  • compose component boundaries
  • define interaction model
  • use platform libraries
  • optimize execution
  • enforce security

2. Choose the right data access pattern

NeedDefault pattern
single-record UILDS / getRecord
simple CRUD formbase record form components
complex server queryApex @AuraEnabled(cacheable=true)
related graph dataGraphQL wire adapter
cross-DOM communicationLightning Message Service

3. Start from an asset when useful

Use provided assets for:

  • basic component bundles
  • datatables
  • modal patterns
  • Flow screen components
  • GraphQL components
  • LMS message channels
  • Jest tests
  • TypeScript-enabled components

4. Validate for frontend quality

Check:

  • accessibility
  • SLDS 2 / dark mode compliance
  • event contracts
  • performance / rerender safety
  • Jest coverage when required

5. Hand off supporting backend or deploy work

Use:


High-Signal Rules

  • prefer platform base components over reinventing controls
  • use @wire for reactive read-only use cases; imperative calls for explicit actions and DML paths
  • do not introduce inaccessible custom UI
  • avoid hardcoded colors; use SLDS 2-compatible styling hooks / variables
  • avoid rerender loops in renderedCallback()
  • keep component communication patterns explicit and minimal

Output Format

When finishing, report in this order:

  1. Component(s) created or updated
  2. Data access pattern chosen
  3. Files changed
  4. Accessibility / styling / testing notes
  5. Next implementation or deploy step

Suggested shape:

text
LWC work: <summary>
Pattern: <wire / apex / graphql / lms / flow-screen>
Files: <paths>
Quality: <a11y, SLDS2, dark mode, Jest>
Next step: <deploy, add controller, or run tests>

Local Development Server

Preview LWC components locally with hot reload — no deployment needed. Run the commands in scripts/local-dev-preview.sh to start a local dev session for a component, app, or Experience Cloud site.

Local Dev commands install just-in-time on first run. They are long-running processes that open a browser with live preview. Changes to .js, .html, and .css files auto-reload instantly. Requires an active org connection for data and Apex callouts.


Cross-Skill Integration

NeedDelegate toReason
Apex controller or serviceplatform-apex-generatebackend logic
embed in Flow screensautomation-flow-generatedeclarative orchestration
deploy component bundleplatform-metadata-deployorg rollout
create supporting metadata (message channels, objects)platform-metadata-deploymetadata deployment

Reference File Index

Start here

Accessibility / performance / state

Integration / advanced features

Asset templates

Scripts


Score Guide

ScoreMeaning
150+production-ready LWC bundle
125–149strong component with minor polish left
100–124functional but review recommended
< 100needs significant improvement

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Experience Lwc Generate AI skill do?

Lightning Web Components with PICKLES methodology and 165-point scoring. Use this skill when the user creates or edits LWC components, builds wire service patterns, or writes Jest tests for LWC. TRIGGER when: user creates/edits LWC components, touches lwc/**/*.js, .html, .css, .js-meta.xml files, or asks about wire service, SLDS, or Jest LWC tests. DO NOT TRIGGER when: Apex classes (use platform-apex-generate), Aura components, or Visualforce.

Why use Experience Lwc Generate on TypingMind?

Because you install it once and use it with any model. Experience Lwc Generate is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Experience Lwc Generate in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/forcedotcom/sf-skills/tree/main/plugins/builder/experience-lwc/skills/experience-lwc-generate. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Experience Lwc Generate?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Experience Lwc Generate?

As many as you like. As long as a model supports skills, you can use Experience Lwc Generate with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Experience Lwc Generate AI skill free?

Yes. It is published on GitHub by forcedotcom under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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