scan_text_nodes

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Overview

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Parameters

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Response

• success (boolean) - Whether the scan completed successfully
• totalNodes (number) - Total number of text nodes found
• processedNodes (number) - Number of nodes processed
• chunks (number) - Number of chunks the operation was divided into
• textNodes (array) - Array of text node objects with the following properties:
  • id (string) - Node ID
  • name (string) - Node name in Figma
  • characters (string) - Text content
  • bbox (object) - Bounding box with x, y, width, height
  • style (object) - Text styling information (fontFamily, fontSize, fontWeight, etc.)

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Chunking Behavior

• Chunk Size: Processes 10 nodes at a time
• Progress Updates: Sends real-time progress updates during processing
• Non-Blocking: Prevents Figma UI from freezing during large scans
• Automatic: Chunking is enabled by default for all scans

• Current chunk being processed
• Number of nodes processed so far
• Estimated completion percentage

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Example

const result = await scan_text_nodes({
  nodeId: "123:456"
});

console.log(`Found ${result.totalNodes} text nodes`);
console.log(`Processed in ${result.chunks} chunks`);

// Access individual text nodes
result.textNodes.forEach(node => {
  console.log(`${node.name}: ${node.characters}`);
});

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Use Cases

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Text Inventory

const textNodes = await scan_text_nodes({ nodeId: "frame-id" });
const labels = textNodes.textNodes.filter(n => n.name.includes("Label"));

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Localization Preparation

const allText = await scan_text_nodes({ nodeId: "screen-id" });
const textToTranslate = allText.textNodes.map(node => ({
  id: node.id,
  content: node.characters,
  context: node.name
}));

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Design Audit

const result = await scan_text_nodes({ nodeId: "page-id" });
const fontUsage = result.textNodes.reduce((acc, node) => {
  const font = node.style.fontFamily;
  acc[font] = (acc[font] || 0) + 1;
  return acc;
}, {});

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Performance Considerations

• Large Designs: For frames with 500+ text nodes, expect processing time of 5-10 seconds
• Progress Tracking: Monitor progress updates to track scanning status
• Memory Efficient: Chunking ensures memory usage stays reasonable even for large designs
• Network Overhead: Each progress update is sent over WebSocket, so very large designs may have higher network traffic

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Best Practices

1. Scope Appropriately: Scan specific frames rather than entire pages when possible
2. Monitor Progress: Use progress updates to inform users during long scans
3. Cache Results: Store scan results if you need to reference them multiple times
4. Combine with Filtering: Use the results with array methods to find specific text nodes

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Related Tools

• set_text_content - Update a single text node
• set_multiple_text_contents - Update multiple text nodes in batch
• scan_nodes_by_types - Scan for nodes of specific types