| list_pages | List all pages in a Figma file. HOW IT WORKS: Returns compact JSON with page names, IDs, and frame counts Large files (>50 pages) are automatically chunked Use 'continue: true' to get next batch
TYPICAL WORKFLOW: list_pages → see all pages list_frames(page_name) → see frames in a page get_frame_info(frame_name) → detail one frame
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| list_frames | List frames/screens in a specific page. HOW IT WORKS: Search by page name (partial match supported) Large pages (>50 frames) are automatically chunked Returns compact list with frame names, sizes, and IDs Session remembers what was sent
TYPICAL WORKFLOW: list_pages → find page name list_frames(page_name) → see frames get_frame_info(frame_name) → detail one frame extract_assets(frame_name) → get assets
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| get_frame_info | Get detailed info about a specific frame. IMPORTANT: This should be your FIRST call for any implementation task.
Always call get_frame_info BEFORE taking screenshots to understand the structure. HOW IT WORKS: Returns all components, text, colors, and styles Large frames (>1000 elements) trigger warning with strategy Use depth parameter to control detail level Automatically chunks if response too large
The tree includes special markers: TYPICAL WORKFLOW: list_frames → find frame name get_frame_info(frame_name) → structure extract_styles → design tokens extract_assets → icons/images
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| get_screenshot | Capture screenshot of a frame. WARNING: Do NOT use screenshots as the first step!
Always call get_frame_info first to understand the structure.
Screenshots are for visual reference AFTER you understand the tree. HOW IT WORKS: TYPICAL WORKFLOW: list_frames → find frame get_frame_info → structure details get_screenshot → visual reference
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| extract_styles | Extract all design tokens from a frame. HOW IT WORKS: Collects colors, fonts, spacing, border radius, shadows Returns organized JSON ready for CSS/theme generation No chunking needed (compact output)
TYPICAL WORKFLOW: get_frame_info → understand structure extract_styles → design tokens Use tokens to build theme/CSS
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| extract_assets | Extract all assets from a frame with progress tracking. HOW IT WORKS: Detects "composite groups" (image + decorative shapes) and exports them as single PNG For composite groups, the ENTIRE group is exported as one image, preserving layout Automatically categorizes into icons/, images/, and images/composites/ Uses smart naming based on component hierarchy Shows progress: "Processing batch 1/5 - found 8 icons, 3 images, 2 composites" Final summary with all file paths Look for "isCompositeAsset: true" in the frame tree to identify composite groups
TYPICAL WORKFLOW: get_frame_info → see what assets exist and identify composite groups extract_assets → download all Check summary for file paths
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| search_components | Search for components by name across the file. HOW IT WORKS: Searches entire file or specific page Returns top 20 results with total count If >20 results, suggests refinement options Use 'continue: true' to get more results
TYPICAL WORKFLOW: search_components(query) → find matches If too many: refine with page_name or type filter get_frame_info on specific result
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| get_file_styles | Get all published styles defined in the file. HOW IT WORKS: Returns design system tokens: colors, text styles, effects These are the official styles defined in Figma Compact output, no chunking needed
TYPICAL WORKFLOW: get_file_styles → global design tokens extract_styles(frame) → frame-specific tokens Combine for complete design system
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| repeat_last | Repeat the last response without making new API calls. HOW IT WORKS: WHEN TO USE: |
| get_session_state | Get current session state for debugging. RETURNS: Current file being explored Pages and frames already sent Pending continuation operations Last update timestamp
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| reset_session | Clear all session state for fresh start. USE WHEN: Switching to different Figma file Want to re-explore from scratch Session state seems corrupted
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| analyze_page_structure | Analyze page structure BEFORE any implementation. MUST BE CALLED FIRST for any large page/frame. HOW IT WORKS: Identifies sections by background color changes Detects transition elements spanning multiple sections Groups icons by section Estimates token usage Recommends agent count for parallel work
RETURNS: sections: List with id, name, bgColor, bounds, complexity transition_elements: Elements spanning multiple sections icons_by_section: Icons organized by section total_estimated_tokens: Token estimate for full frame recommended_division: 'single' or 'multiple' recommended_agent_count: How many agents to use
TYPICAL WORKFLOW: analyze_page_structure → understand structure If recommended_division='multiple': use get_section_screenshot Each agent uses get_agent_context for its section
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| get_section_screenshot | Capture screenshot of a specific section within a frame. HOW IT WORKS: First call analyze_page_structure to identify sections Makes other sections transparent (shows only target section) Optionally includes transition elements context Returns cropped image focused on section Useful for parallel analysis of large frames
TYPICAL WORKFLOW: analyze_page_structure → identify sections get_section_screenshot(sectionId) → capture isolated section get_frame_info with section context → implementation details
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| get_agent_context | Prepare agent context for parallel implementation of a section. HOW IT WORKS: Call after analyze_page_structure to identify sections Returns complete context for a single agent to implement one section Handles responsibilities: what to implement vs coordinate Includes icons, styles, and transition element info Generates agent-specific instructions with coordination rules
RETURNS: section: Details (id, name, background color, bounds) responsibilities: what agent implements, coordinates, or skips assets: icons and images in this section styles: colors, fonts, spacing specific to section agent_info: index, total agents, is_first, is_last instructions: detailed markdown instructions for this agent
TYPICAL WORKFLOW: analyze_page_structure → identify sections For each section: get_section_screenshot → visual reference get_agent_context(sectionId, agentIndex) → agent-specific context Each agent implements using provided context
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| get_full_page_context | Get complete page context in ONE call with all sections, assets, screenshots, and styles. WHAT YOU GET IN ONE CALL: Complete page structure with all sections identified Screenshots for each section (base64 encoded) All assets organized by section with unique names Design tokens per section Asset map for quick lookup Agent instructions ready for parallel implementation Transition elements that span multiple sections
PERFECT FOR: Getting full context before implementation Preparing data for parallel multi-agent work Quick assessment of page complexity One-call solution for complete page understanding
RETURNS: overview: Frame metadata and recommendations sections: Array with all section details including screenshots assetMap: Quick lookup table for assets by unique name agentInstructions: Pre-written instructions for each agent transitionElements: Elements spanning multiple sections
TYPICAL WORKFLOW: get_full_page_context → get everything at once Distribute sections to multiple agents using agentInstructions Each agent implements their section with all necessary context
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