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Figma · Design · Data Analysis / AGENT SKILL

understand-figma

egonex-ai/understand-anything
1.2K installs 83.9K GitHub stars
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Analyze Figma files and generate interactive knowledge graphs of screens, components, and design tokens.
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.

BEFORE YOU INSTALL

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The full skill.

Original instructions from the publisher’s SKILL.md

# /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 `$PROJECT_ROOT`, re-resolving it with the same line if a later command block needs it.
3. Resolve `PLUGIN_ROOT` and ensure core is built (same logic as `/understand` Phase 0.1.5). If `packages/core/dist/figma/index.js` is missing, run:
   ```bash
   cd "$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):

```bash
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

```bash
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`:
   ```bash
   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.