figma-reference-architecture
Reference architecture for production Figma API integrations. Use when designing a new Figma integration, planning project structure, or establishing patterns for design-to-code pipelines. Trigger with phrases like "figma architecture", "figma project structure", "figma integration design", "figma best practices layout".
Best use case
figma-reference-architecture is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Reference architecture for production Figma API integrations. Use when designing a new Figma integration, planning project structure, or establishing patterns for design-to-code pipelines. Trigger with phrases like "figma architecture", "figma project structure", "figma integration design", "figma best practices layout".
Teams using figma-reference-architecture should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/figma-reference-architecture/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How figma-reference-architecture Compares
| Feature / Agent | figma-reference-architecture | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Reference architecture for production Figma API integrations. Use when designing a new Figma integration, planning project structure, or establishing patterns for design-to-code pipelines. Trigger with phrases like "figma architecture", "figma project structure", "figma integration design", "figma best practices layout".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
Best AI Skills for Claude
Explore the best AI skills for Claude and Claude Code across coding, research, workflow automation, documentation, and agent operations.
ChatGPT vs Claude for Agent Skills
Compare ChatGPT and Claude for AI agent skills across coding, writing, research, and reusable workflow execution.
SKILL.md Source
# Figma Reference Architecture
## Overview
Production-ready architecture for Figma REST API integrations. Covers the three most common use cases: design token pipelines, asset export systems, and webhook-driven automation.
## Prerequisites
- Understanding of Figma REST API endpoints
- TypeScript project setup
- Decision on deployment platform
## Instructions
### Step 1: Project Structure
```
figma-integration/
├── src/
│ ├── figma/
│ │ ├── client.ts # Typed REST API wrapper
│ │ ├── types.ts # Figma API response types
│ │ ├── errors.ts # FigmaApiError, FigmaRateLimitError
│ │ ├── cache.ts # LRU cache for API responses
│ │ └── walker.ts # Node tree traversal utilities
│ ├── services/
│ │ ├── token-extractor.ts # Design token extraction
│ │ ├── asset-exporter.ts # Image/icon export pipeline
│ │ ├── comment-syncer.ts # Comment sync to Slack/Jira
│ │ └── variable-syncer.ts # Variables API sync (Enterprise)
│ ├── webhooks/
│ │ ├── handler.ts # Webhook event router
│ │ ├── verify.ts # Passcode verification
│ │ └── processors/
│ │ ├── file-update.ts # FILE_UPDATE handler
│ │ ├── comment.ts # FILE_COMMENT handler
│ │ └── library.ts # LIBRARY_PUBLISH handler
│ ├── api/
│ │ ├── health.ts # Health check endpoint
│ │ ├── tokens.ts # Token API endpoint
│ │ └── assets.ts # Asset download endpoint
│ └── index.ts
├── scripts/
│ ├── extract-tokens.mjs # CLI: extract tokens from Figma
│ ├── export-icons.mjs # CLI: export icons from Figma
│ └── setup-webhooks.mjs # CLI: create/manage webhooks
├── output/
│ ├── tokens.css # Generated CSS custom properties
│ ├── tokens.json # Generated JSON tokens
│ └── icons/ # Exported SVG/PNG icons
├── tests/
│ ├── fixtures/ # Saved Figma API responses
│ └── *.test.ts
├── .env.example
└── package.json
```
### Step 2: Data Flow Architecture
```
┌────────────────────────────────────────────────┐
│ Figma Cloud │
│ ┌──────────┐ ┌──────────┐ ┌──────────────┐ │
│ │ Files API │ │Images API│ │ Webhooks V2 │ │
│ │ /v1/files │ │/v1/images│ │ /v2/webhooks │ │
│ └─────┬─────┘ └────┬─────┘ └──────┬───────┘ │
└────────┼──────────────┼───────────────┼─────────┘
│ │ │
┌────▼────┐ ┌────▼────┐ ┌─────▼────┐
│ Token │ │ Asset │ │ Webhook │
│Extractor│ │Exporter │ │ Handler │
└────┬────┘ └────┬────┘ └─────┬────┘
│ │ │
┌────▼────┐ ┌────▼────┐ ┌─────▼────┐
│ Cache │ │ Cache │ │ Event │
│ (LRU) │ │ (URLs) │ │ Queue │
└────┬────┘ └────┬────┘ └─────┬────┘
│ │ │
┌────▼──────────────▼───────────────▼────┐
│ Output Layer │
│ tokens.css │ icons/ │ Slack/Jira │
└─────────────────────────────────────────┘
```
### Step 3: Key Components
**Figma Client** (see `figma-sdk-patterns`):
```typescript
// Singleton with retry, rate limit handling, and caching
const client = new FigmaClient(process.env.FIGMA_PAT!);
// All API calls go through the client
const file = await client.getFile(fileKey); // GET /v1/files/:key
const nodes = await client.getFileNodes(fileKey, ids); // GET /v1/files/:key/nodes
const images = await client.getImages(fileKey, ids); // GET /v1/images/:key
const comments = await client.getComments(fileKey); // GET /v1/files/:key/comments
const vars = await client.getLocalVariables(fileKey); // GET /v1/files/:key/variables/local
```
**Token Extraction Pipeline** (see `figma-core-workflow-a`):
```typescript
// file → styles → nodes → CSS/JSON tokens
export async function extractTokens(fileKey: string): Promise<DesignToken[]> {
const file = await client.getFile(fileKey);
const styleNodes = await client.getFileNodes(fileKey, Object.keys(file.styles));
return parseTokensFromNodes(file.styles, styleNodes);
}
```
**Asset Export Pipeline** (see `figma-core-workflow-b`):
```typescript
// file → find components → render images → download
export async function exportIcons(fileKey: string, frameId: string) {
const frame = await client.getFileNodes(fileKey, [frameId]);
const componentIds = findComponents(frame).map(n => n.id);
const imageUrls = await client.getImages(fileKey, componentIds, { format: 'svg' });
return downloadAll(imageUrls);
}
```
**Webhook Handler** (see `figma-webhooks-events`):
```typescript
// Verify passcode → route event → process async
export function webhookRouter(event: FigmaWebhookEvent) {
switch (event.event_type) {
case 'FILE_UPDATE': return handleFileUpdate(event);
case 'LIBRARY_PUBLISH': return handleLibraryPublish(event);
case 'FILE_COMMENT': return handleComment(event);
}
}
```
### Step 4: Configuration
```typescript
// src/config.ts
export const config = {
figma: {
token: process.env.FIGMA_PAT!,
fileKey: process.env.FIGMA_FILE_KEY!,
webhookPasscode: process.env.FIGMA_WEBHOOK_PASSCODE,
},
cache: {
fileTTL: 5 * 60 * 1000, // 5 minutes for file metadata
imageTTL: 24 * 60 * 60 * 1000, // 24 hours for image URLs
maxEntries: 500,
},
api: {
maxConcurrent: 3,
retryAttempts: 3,
requestTimeout: 30_000,
},
};
```
## Output
- Structured project layout with clear separation
- Data flow from Figma API to local artifacts
- Reusable client, cache, and pipeline components
- Configuration management for all environments
## Error Handling
| Layer | Error | Recovery |
|-------|-------|----------|
| Client | 429 Rate Limited | Retry with `Retry-After` header |
| Client | 403 Forbidden | Alert on token expiry; fail gracefully |
| Cache | Cache miss storm | Stale-while-revalidate pattern |
| Webhook | Duplicate events | Idempotency via event timestamp |
| Export | Image render null | Skip node, log warning |
## Resources
- [Figma REST API](https://developers.figma.com/docs/rest-api/)
- [Figma REST API OpenAPI Spec](https://github.com/figma/rest-api-spec)
- [Figma Webhooks V2](https://developers.figma.com/docs/rest-api/webhooks/)
## Next Steps
For multi-environment setup, see `figma-multi-env-setup`.Related Skills
workhuman-reference-architecture
Workhuman reference architecture for employee recognition and rewards API. Use when integrating Workhuman Social Recognition, or building recognition workflows with HRIS systems. Trigger: "workhuman reference architecture".
wispr-reference-architecture
Wispr Flow reference architecture for voice-to-text API integration. Use when integrating Wispr Flow dictation, WebSocket streaming, or building voice-powered applications. Trigger: "wispr reference architecture".
windsurf-reference-architecture
Implement Windsurf reference architecture with optimal project structure and AI configuration. Use when designing workspace configuration for Windsurf, setting up team standards, or establishing architecture patterns that maximize Cascade effectiveness. Trigger with phrases like "windsurf architecture", "windsurf project structure", "windsurf best practices", "windsurf team setup", "optimize for cascade".
windsurf-architecture-variants
Choose workspace architectures for different project scales in Windsurf. Use when deciding how to structure Windsurf workspaces for monorepos, multi-service setups, or polyglot codebases. Trigger with phrases like "windsurf workspace strategy", "windsurf monorepo", "windsurf project layout", "windsurf multi-service", "windsurf workspace size".
webflow-reference-architecture
Implement Webflow reference architecture — layered project structure, client wrapper, CMS sync service, webhook handlers, and caching layer for production integrations. Trigger with phrases like "webflow architecture", "webflow project structure", "how to organize webflow", "webflow integration design", "webflow best practices".
vercel-reference-architecture
Implement a Vercel reference architecture with layered project structure and best practices. Use when designing new Vercel projects, reviewing project structure, or establishing architecture standards for Vercel applications. Trigger with phrases like "vercel architecture", "vercel project structure", "vercel best practices layout", "how to organize vercel project".
vercel-architecture-variants
Choose and implement Vercel architecture blueprints for different scales and use cases. Use when designing new Vercel projects, choosing between static, serverless, and edge architectures, or planning how to structure a multi-project Vercel deployment. Trigger with phrases like "vercel architecture", "vercel blueprint", "how to structure vercel", "vercel monorepo", "vercel multi-project".
veeva-reference-architecture
Veeva Vault reference architecture for REST API and clinical operations. Use when working with Veeva Vault document management and CRM. Trigger: "veeva reference architecture".
vastai-reference-architecture
Implement Vast.ai reference architecture for GPU compute workflows. Use when designing ML training pipelines, structuring GPU orchestration, or establishing architecture patterns for Vast.ai applications. Trigger with phrases like "vastai architecture", "vastai design pattern", "vastai project structure", "vastai ml pipeline".
twinmind-reference-architecture
Production architecture for meeting AI systems using TwinMind: transcription pipeline, memory vault, action item workflow, and calendar integration. Use when implementing reference architecture, or managing TwinMind meeting AI operations. Trigger with phrases like "twinmind reference architecture", "twinmind reference architecture".
together-reference-architecture
Together AI reference architecture for inference, fine-tuning, and model deployment. Use when working with Together AI's OpenAI-compatible API. Trigger: "together reference architecture".
techsmith-reference-architecture
TechSmith reference architecture for Snagit COM API and Camtasia automation. Use when working with TechSmith screen capture and video editing automation. Trigger: "techsmith reference architecture".