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Understand figma

Skill Egonex-AI/Understand-Anything/understand-anything-plugin/skills/understand-figma

Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.

Install
npx -y skills add Egonex-AI/Understand-Anything --skill understand-figma

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What its author says it does

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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.

SKILL.md

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/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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