/understand-figma

SkillFiles & storage

Understand-figma lets your AI analyze a Figma file and turn it into an interactive design knowledge graph. The graph lays out the file's pages, screens, components, component sets, instances, and design tokens, all viewable in a design dashboard. Once added, your agent can map how a design is organized without you clicking through the file yourself.

Available today. Use it from your connected AI after setup.

Add the skill, then ask your agent to analyze a Figma file. It will build the knowledge graph and open the design dashboard so you can browse the design's structure.

Then ask your AI: use the /understand-figma skill

What your AI can do with it

  • Analyze a Figma file and extract its structure
  • Map pages and screens into an interactive knowledge graph
  • Catalog components, component sets, and instances
  • Pull out the design tokens used across the file
  • Open an interactive design dashboard to explore the results

What this skill tells your AI

The instructions your AI receives, as published by egonex-ai/understand-anything in understand-anything-plugin/skills/understand-figma/SKILL.md and read by ahel’s review.

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.

Signals

GitHub stars
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Forks
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Last commit
Sep 2026

ahel review

  • S4info
    community integration — published by egonex-ai, not figma

Automated review, not a security audit. Ruleset v1.

Advanced
Catalog kind
skill
Gateway key
understand-figma
Source
github.com/egonex-ai/understand-anything