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understand-figma

Analyze a Figma file and turn its pages, screens, components, instances, and design tokens—shared design values—into an interactive graph. Open the dashboard to explore the file's structure and relationships.

OriginalShow the original description

Analyze a Figma file via the Figma REST API and generate an interactive design knowledge graph (pages, screens, components, component sets, instances, design tokens) with a kind:"design" dashboard.

Works withFigma
AI rating80/ 100See how to install

Good for

  • Review the structure of a Figma file
  • Explore components, variants, and instances
  • Inspect how shared design values are used
  • Analyze a design with a specified output language

Overview

What it does

Analyzes a Figma file and maps relationships between pages, screens, components, component sets that group variants, and placed instances. It also covers design tokens, which represent shared values such as colors. It combines structure retrieved through the Figma REST API with AI analysis, saves a design knowledge graph, and opens an interactive dashboard.

When it helps

Use it to understand a whole Figma file, organize relationships between its parts, or examine how shared values are used. After analysis, you can check counts of elements by type and summaries of their relationships. If the same file version has already been analyzed, it reports that status. You can also specify the output language.

Example requests

  • “Map the design structure and component relationships from this Figma file URL.”
  • “Analyze this file with /understand-figma <figma-file-url-or-key> --language en.”

Notes

Set a Figma personal access token in the FIGMA_TOKEN environment variable. Node 22 or later and pnpm 10 or later are required. Processing contacts api.figma.com, so it is not fully offline. The token is sent in a request header; the design keeps it out of the graph, logs, and intermediate files.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Objective evaluation

AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.

Clear instructionsIs it clear when to use it and what it does?
AGoodIt explicitly analyzes a Figma file and produces a design knowledge graph and dashboard.
Concrete stepsAre steps, inputs, outputs, and examples spelled out?
AGoodFetching, analysis, merging, and saving are specified, with executable scripts and named output files.
SafetyAre sending data, deleting files, and running commands disclosed?
CCheck firstIt deletes intermediate directory entries other than scan-manifest.json using rm -rf without a confirmation step.
Easy setupDoes it need few tools or API keys, and are they documented?
AGoodIt provides FIGMA_TOKEN setup, required Node and pnpm versions, and installation and build commands.

The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 21, 2026. Treat it as a guide and read the original before installing.

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Files included (3)

  • SKILL.md4.0 KB
  • figma-merge.mjs1.7 KB
  • figma-scan.mjs4.2 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

/understand-figma

Analyzes a Figma file and produces an interactive design knowledge graph in the existing dashboard.

Prerequisites

  • FIGMA_TOKEN environment variable — a Figma personal access token (create one at https://www.figma.com/settings). If it is missing, STOP and tell the user:

    Set a Figma token first: create one at figma.com/settings, then export FIGMA_TOKEN=<token>.

  • Node ≥ 22, pnpm ≥ 10.

Security: the token is read only from the environment and travels only in the X-Figma-Token request header. Never write it to the graph, meta.json, logs, or intermediate files. This skill makes outbound calls to api.figma.com — unlike /understand, it is not fully offline. Tell the user this once.

Phase 0 — Pre-flight

  1. Parse $ARGUMENTS for a Figma URL or bare file key (the non-flag token) and an optional --language <lang>.
  2. Resolve PROJECT_ROOT to the current working directory. Resolve the data directory $UA_DIR once and reuse it for every read and write below: UA_DIR="$PROJECT_ROOT/$([ -d "$PROJECT_ROOT/.understand-anything" ] && echo .understand-anything || echo .ua)" — the legacy .understand-anything/ when it already exists, otherwise the new .ua/. Because each phase may run in a fresh shell, carry $UA_DIR forward like $PROJECT_ROOT, re-resolving it with the same line if a later command block needs it.
  3. Resolve PLUGIN_ROOT and ensure core is built (same logic as /understand Phase 0.1.5). If packages/core/dist/figma/index.js is missing, run:
    cd "$PLUGIN_ROOT" && (pnpm install --frozen-lockfile 2>/dev/null || pnpm install) && pnpm --filter @understand-anything/core build
    
  4. mkdir -p $UA_DIR/intermediate.

Phase 1 — FETCH & PARSE (deterministic)

Run the bundled scan script (<SKILL_DIR> is this skill's directory):

FIGMA_TOKEN="$FIGMA_TOKEN" node <SKILL_DIR>/figma-scan.mjs "$PROJECT_ROOT" "<url-or-key>"

It writes $UA_DIR/intermediate/scan-manifest.json and prints the node counts. Relay the counts to the user. If it exits non-zero, relay stderr and STOP.

If the scan prints UP_TO_DATE, report "Design graph is already up to date for this Figma file version" and STOP. To force a full rebuild, re-run with UNDERSTAND_FIGMA_FORCE=1 set in the environment.

Phase 2 — ANALYZE (LLM enrichment)

  1. Read scan-manifest.json. Group nodes into batches of ~15, grouped by page when possible.
  2. For each batch, dispatch a subagent using the design-analyzer agent definition (agents/design-analyzer.md). Pass:
    • the batch of nodes (id, type, name, figmaMeta, child names, token usage),
    • the full list of existing node IDs,
    • $INTERMEDIATE_DIR = $UA_DIR/intermediate,
    • the batch number for output naming. The agent writes analysis-batch-<N>.json. Append $LANGUAGE_DIRECTIVE if --language was provided (reuse /understand's directive text).
  3. Run up to 5 batches concurrently. If a batch fails, log a warning and continue — the manifest is a solid base.

Phase 3 — MERGE

node <SKILL_DIR>/figma-merge.mjs "$PROJECT_ROOT"

It combines scan-manifest.json + analysis-batch-*.json, runs mergeDesignGraph (validates, re-attaches kind:"design"), and writes knowledge-graph.json + meta.json. Relay the printed stats and any non-auto-corrected issues.

Phase 4 — SAVE & LAUNCH

  1. Clean up intermediate files except scan-manifest.json:
    INTER="$UA_DIR/intermediate"
    find "$INTER" -mindepth 1 -maxdepth 1 -not -name 'scan-manifest.json' -exec rm -rf {} +
    
  2. Report a summary: project name, counts by node type, edges by type, layers, tour steps, and the path $UA_DIR/knowledge-graph.json.
  3. Auto-launch the dashboard by invoking the /understand-dashboard skill.

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