Experience Lwc Design Generate logo

Experience Lwc Design Generate

OrganizationPopular
forcedotcom
experience-lwc-design-generate

Use when you need to create a brand new Lightning Web Component from a Figma design, a Product Requirements Document, or another design artifact — orchestrating the five-phase workflow (gather requirements → generate code → optimize → lint/format/compile → test) and stitching together the specialized skills for SLDS, LDS, base components, optimization, and testing. Use this skill whenever the user mentions building a new LWC from Figma, building an LWC from a PRD, generating an LWC from a design or screenshot, or migrating an Aura component as a fresh LWC build. DO NOT TRIGGER when refactoring an existing LWC (use experience-lwc-generate), for Aura → LWC in-place migration (out of scope for this skill), for standalone SLDS token or styling work (use design-systems-slds-apply), or for standalone data-layer work (use experience-lds-best-practices-apply or experience-lds-data-requirements-generate).

Overview

Publisherforcedotcom
Repositorysf-skills
Skill nameexperience-lwc-design-generate
Stars
1.1K
Forks
351
Bundled files
4
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.

  • 4 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 Design 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-design-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-design-generate .claude/skills/experience-lwc-design-generate
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Experience Lwc Design 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 Design 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 Design 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.

Creating LWC Components from Design

Orchestrate the end-to-end creation of a new Lightning Web Component from a design input (Figma, PRD, Aura source, or user description). This is the top-level workflow skill — it sequences the specialized sibling skills that own each stage. Org-aware data (LDS schema introspection, design-frame inspection) is resolved by handing off to experience-lds-data-requirements-generate or via design-tool URLs the user provides.

When to Use

  • Building a brand-new LWC from a Figma frame, PRD, or written spec.
  • Migrating an Aura component to LWC as a fresh build (in-place Aura → LWC porting is out of scope for this skill).
  • Creating a component whose requirements are still partly implicit and need distillation into a PRD before coding.

Do NOT use this skill for:

  • Refactoring an existing LWC (use experience-lwc-generate).
  • Aura → LWC in-place migration (out of scope for this skill).
  • Pure styling or data-layer work (use the specialized skills directly).

Prerequisites

  • At least one design input: Figma URL, PRD markdown, Aura component source, or a textual spec.
  • Target path (module folder) for the new LWC.
  • For data-backed components: access to the org so experience-lds-data-requirements-generate and experience-lds-best-practices-apply can resolve the schema and adapter shapes.

Knowledge Bases

  • references/prd-analysis-template.md — PRD section skeleton (copy it verbatim when producing a PRD).
  • references/figma-to-prd-blueprint.md — Figma-specific guidance for translating a frame into PRD sections (componentName/tagName, contentRequirements, dataRequirements, interactions, componentCommunication, states, accessibility/responsiveness/styling/localization/security). Read this before Phase 1.2 when the input is a Figma design.

Workflow (mandatory five phases)

Phase 1 — Gather PRD & requirements

Goal: produce a consolidated PRD that every later phase consumes.

  1. Obtain raw requirements — collect the PRD, design spec, Figma URL, Aura source, or user text.

  2. Figma → PRD (if applicable): follow references/figma-to-prd-blueprint.md for the full Figma-frame analysis and PRD section guidelines. Inputs you need from the user: the Figma URL, a screenshot of the target frame, and (if Dev Mode is available) the metadata export for the node. Translate into the PRD skeleton from references/prd-analysis-template.md using the section-by-section guidance in the blueprint.

  3. Aura → PRD (if migrating): enumerate the Aura component's functionality that must be preserved — markup, controller/helper actions, events, attributes, and wired data — and feed that inventory into the PRD as explicit requirements. (In-place Aura → LWC porting is out of scope; this step only captures behavior for a fresh build.)

  4. Data requirements (if the component reads/writes data): hand off to experience-lds-data-requirements-generate. That skill produces a validated data specification (object/field API names, recommended LDS API, implementation approach). Paste its output verbatim into the PRD.

  5. Adapter exploration: hand off to experience-lds-best-practices-apply for the adapter selection rules (UI API vs GraphQL vs Apex) and the recommended wiring for the chosen approach.

  6. Naming: componentName must be camelCase (e.g., productCard) and tagName must be its kebab-case form (e.g., product-card). Validate both with the bundled script — do not eyeball the check:

    bash
    "<skill_dir>/scripts/check-component-name.sh" <componentName> <tagName>

    The script exits nonzero (with an actionable stderr message) if either name is malformed or if the kebab form of componentName does not equal tagName.

Deliverable: a comprehensive PRD covering purpose, content, data, interactions, states, a11y, responsiveness, styling direction, localization, and security. Keep it checked into the workspace (e.g., packages/skills/<skill>-workspace/<iteration>/PRD.md).

Phase 2 — Generate component code

Goal: initial .html, .js, .css, .js-meta.xml that strictly reflect the PRD.

  1. Hand off to experience-lwc-generate with the PRD content as the spec. That skill owns PRD → code translation (events, getters, @api, .js-meta.xml, AI metadata) and is the authoring source of truth.
  2. Use the SLDS decision hierarchy from design-systems-slds-apply:
    1. Prefer a matching Lightning Base Component (experience-lwc-base-components-integrate).
    2. Otherwise pick an SLDS Blueprint or utility class (per design-systems-slds-apply).
    3. Otherwise write custom CSS using SLDS styling hooks (also covered in design-systems-slds-apply).
  3. Re-confirm the authoring baseline by walking the experience-lwc-generate checklist before proceeding.
  4. Translate every PRD data requirement to either a wire adapter (UIAPI / GraphQL) or an explicit TODO.
  5. Adhere strictly to the PRD:
    • Only include features and behaviors the PRD describes.
    • Mark uncertain areas with // TODO: comments that quote the PRD language raising the ambiguity.
    • Add extensive code comments explaining intent.
    • Do not split the component into more sub-components than the PRD implies.

Deliverable: a first-pass LWC bundle in the target path.

Phase 3 — Optimize component

Goal: apply performance, maintainability, and best-practice fixes.

  1. Walk the optimization checklist below before any other review:
    • Single responsibility, encapsulation, reusability.
    • Minimize DOM operations; batch updates via properties.
    • Audit event handlers and lifecycle hook usage (renderedCallback guards).
    • Consider lazy loading for heavy children.
  2. Hand off to experience-lwc-generate for the LWC best-practices review pass (anti-patterns, reactivity, composition).
  3. Hand off to the compliance suite for the pre-ship review — experience-accessibility-validate (a11y), experience-lwc-security-validate (LWS + Product Security), and experience-lwc-rtl-validate (RTL i18n). Run them together for the full quality pass.
  4. If the component touches data, hand off to experience-lds-best-practices-apply for cache/consistency and referential-integrity checks.
  5. Apply every accepted finding. Keep the PRD as the source of truth — do not add scope under the guise of optimization.

Phase 4 — Lint, format, compile-check

Condition: only run steps whose tooling is configured in the project.

  1. Detect project tooling — invoke the bundled detection script from the project root and read its <tool>=yes|no lines. Do NOT eyeball package.json / dotfiles in prose:

    bash
    "<skill_dir>/scripts/detect-project-tools.sh" <projectRoot>

    Sample output:

    text
    eslint=yes
    prettier=yes
    cursor-rules=no
    lwc-compiler=yes

    Run the substeps below only for tools reported yes; skip the rest.

  2. ESLint (if eslint=yes) — run and fix all violations.

  3. Prettier (if prettier=yes) — run for consistent formatting.

  4. Cursor rules (if cursor-rules=yes) — apply every rule the project ships.

  5. LWC compiler (if lwc-compiler=yes) — run via local dev server or SFDX; resolve every syntax/template error before moving on.

Deliverable: clean, validated component code.

Phase 5 — Create tests

Hand off to experience-lwc-accessibility-jest-run for automated accessibility Jest coverage; add general-purpose Jest coverage in the same pass following the experience-lwc-generate test guidance, plus UTAM page object generation if the team requires it.

Deliverable: the LWC bundle with a passing test suite at or above the project's coverage threshold.

Definition of Done

A new component built from this workflow is "done" only when every item below is true. Treat this as the canonical readiness checklist — copy it into the PR description so reviewers can confirm each line.

Code completion — no implementation gaps:

  1. Every PRD requirement is either implemented or explicitly annotated with a TODO: and a linked tracking item. No silent gaps.
  2. No TODO, FIXME, or console.log / console.table / alert() left in production paths.
  3. No commented-out code blocks, no empty function bodies, no placeholder values, no dummy data, no unreferenced imports.
  4. No lwc:dom="manual" regions or third-party-library escape hatches without a comment explaining why a native LWC pattern wasn't used.

Compliance and quality:

  1. .js-meta.xml AI metadata passes the audit in experience-lwc-generate (component-wide <ai><description> set, plus an <ai><property name="…" aiDescription="…"/></ai> entry for every @api member exposed through <targetConfig>; no marketing language).
  2. SLDS styling passes design-systems-slds-apply verification — no raw hex / px values, only styling hooks and SLDS utility classes.
  3. Accessibility pass complete: experience-accessibility-validate for source review + experience-lwc-accessibility-jest-run for automated tests, both green.
  4. Security + RTL pass complete: experience-lwc-security-validate + experience-lwc-rtl-validate, both green.

Data + tests:

  1. Data layer verified against the referenced LDS adapters (every wire / imperative call is documented in the PRD's data section and matches one of the adapters from experience-lds-best-practices-apply or experience-lds-data-requirements-generate).
  2. Jest tests green at the required coverage level for the project. New tests cover every @api surface, every dispatched event, and every error path (failed wire, failed apex, validation rejection).
  3. UTAM page objects produced for any UI flow that needs cross-component browser-level testing (skip if not needed).

Cross-References

  • Skills chained by this workflow (in phase order):
    • experience-lds-data-requirements-generate — Phase 1.4 data spec (and Phase 1.5 adapter exploration alongside experience-lds-best-practices-apply).
    • design-systems-slds-apply, experience-lwc-base-components-integrate — Phase 2 styling decisions.
    • experience-lwc-generate — Phase 2 authoring baseline + Phase 3 best-practices review + Phase 5 AI-metadata audit.
    • experience-lds-best-practices-apply — Phase 2/3 data-layer adapter selection and consistency review.
    • experience-accessibility-validate, experience-lwc-security-validate, experience-lwc-rtl-validate — Phase 3 a11y/security/RTL review.
    • experience-lwc-accessibility-jest-run — Phase 5 automated a11y test generation.
    • Optional: add o11y instrumentation as a separate pass once the component stabilizes.
    • experience-lwc-typescript-migrate — optional once JS is green.
    • When the new component ships behind a flag, gate it with a feature flag during rollout.
    • Generate API-surface documentation once the public API is stable (no dedicated skill for this yet).
  • Org-aware inputs used by this workflow:
    • Figma URL + screenshot (and, if available, the developer's Dev Mode metadata export) — Phase 1.2 Figma input.
    • experience-lds-data-requirements-generate owns the org-schema introspection and data-spec validation used in Phase 1 when the component needs org-backed data — hand off to that skill rather than duplicating its work here.

Examples

Phase 1 PRD skeleton (fill from the Figma/PRD/Aura input)

text
Component: productCard (<product-card>)
Purpose: Render a compact summary of a product with quick actions.

Content requirements
- Hero image (Product.HeroImage__c)
- Title (Product.Name)
- Subtitle (Product.Tagline__c)
- Primary CTA button ("Add to cart")
- Secondary CTA icon button ("Favorite")

Data requirements
- Input: @api recordId (Product Id)
- Adapter: getRecord (UIAPI) with fields Name, Tagline__c, HeroImage__c
- Events out: addtocart{detail.recordId}, favorite{detail.recordId, detail.value}

States
- Loading (data not yet resolved)
- Error (adapter error)
- Empty (no record found)
- Default

Accessibility
- Title uses <h3>
- Icon-only button carries aria-label="Favorite"
- Card is a labelled region (role="group", aria-labelledby)

Responsiveness
- Full width < 480px
- Side-by-side image + text >= 480px

Styling
- Uses lightning-card wrapper
- Surface color: --slds-g-color-surface-container-1
- Shadow: --slds-g-shadow-1

Phase 2 skeleton

javascript
import { LightningElement, api, wire } from 'lwc';
import { getRecord } from 'lightning/uiRecordApi';
import NAME from '@salesforce/schema/Product__c.Name';
import TAGLINE from '@salesforce/schema/Product__c.Tagline__c';
import HERO from '@salesforce/schema/Product__c.HeroImage__c';

const FIELDS = [NAME, TAGLINE, HERO];

export default class ProductCard extends LightningElement {
    @api recordId;

    @wire(getRecord, { recordId: '$recordId', fields: FIELDS })
    record;

    get hasRecord() { return this.record?.data != null; }
    get isLoading() { return !this.record; }
    get hasError()  { return !!this.record?.error; }
    get name()      { return this.record?.data?.fields?.Name?.value ?? ''; }
    get tagline()   { return this.record?.data?.fields?.Tagline__c?.value ?? ''; }
    get heroUrl()   { return this.record?.data?.fields?.HeroImage__c?.value ?? ''; }

    handleAddToCart() {
        this.dispatchEvent(new CustomEvent('addtocart', { detail: { recordId: this.recordId }, bubbles: true, composed: true }));
    }
    handleFavorite(event) {
        this.dispatchEvent(new CustomEvent('favorite', { detail: { recordId: this.recordId, value: event.detail.value }, bubbles: true, composed: true }));
    }
}

Verification

  • Every PRD section is traceable to at least one block of code or an explicit TODO.
  • Phases 1–5 were executed in order; no step was skipped.
  • Accessibility, SLDS, data-layer, and AI metadata reviews all pass.
  • Coverage meets or exceeds the project's threshold.
  • The component renders correctly in experience-lwc-runtime-observe across the responsive breakpoints enumerated in the PRD.

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 Design Generate AI skill do?

Use when you need to create a brand new Lightning Web Component from a Figma design, a Product Requirements Document, or another design artifact — orchestrating the five-phase workflow (gather requirements → generate code → optimize → lint/format/compile → test) and stitching together the specialized skills for SLDS, LDS, base components, optimization, and testing. Use this skill whenever the user mentions building a new LWC from Figma, building an LWC from a PRD, generating an LWC from a design or screenshot, or migrating an Aura component as a fresh LWC build. DO NOT TRIGGER when refactor...

Why use Experience Lwc Design Generate on TypingMind?

Because you install it once and use it with any model. Experience Lwc Design 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 Design 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-design-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 Design 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 Design Generate?

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

Is the Experience Lwc Design 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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