Borrowing it
Nothing to install: this file belongs to iress/design-system. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/iress/design-system/main/.agents/skills/figma-to-ids/SKILL.mdgit clone --depth 1 https://github.com/iress/design-systemWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/iress/design-system/figma-to-ids)<a href="https://agentmods.dev/skills/iress/design-system/figma-to-ids"><img src="https://agentmods.dev/badge/skills/iress/design-system/figma-to-ids/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/iress/design-system/figma-to-ids"><img src="https://agentmods.dev/badge/skills/iress/design-system/figma-to-ids.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00060 | $0.04068 |
| Opus 5 | $0.00030 | $0.02034 |
| Sonnet 5 | $0.00012 | $0.00814 |
| Haiku 4.5 | $0.00006 | $0.00407 |
Grade A, and why
figma-to-ids scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 408 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Figma to IDS Translation
Purpose
Translate Figma design properties and structures into IDS (Iress Design System) component implementations. This skill helps AI agents interpret Figma design metadata (from tools like Figma MCP or exported design specs) and produce accurate IDS code.
Figma MCP Setup
AI agents need a Figma MCP server to read Figma files directly. Without one, you can still use this skill by pasting exported design specs or Figma component descriptions manually.
Setup
-
Get a Figma personal access token — In Figma, go to Settings → Account → Personal access tokens and create a token with File content (Read-only) scope.
-
Add the MCP server to your agent config. The exact location depends on your tool:
Tool Config file Kiro CLI ~/.kiro/settings/mcp.json(global) or.kiro/settings/mcp.json(workspace)Cursor .cursor/mcp.jsonClaude Code .claude/mcp.jsonor~/.claude/mcp.jsonVS Code (GitHub Copilot) .vscode/mcp.jsonExample configuration (using the community
figma-developer-mcpserver):{ "mcpServers": { "Figma": { "command": "npx", "args": ["-y", "figma-developer-mcp", "--stdio"], "env": { "FIGMA_API_KEY": "<your-figma-token>" } } } }For Kiro CLI, you can also add it via the command line:
kiro-cli mcp add --name Figma --command npx --args "-y figma-developer-mcp --stdio" --env "FIGMA_API_KEY=<your-figma-token>" -
Verify — Ask your agent to fetch data from a Figma file URL. It should return frame and component information.
Process
- Analyse Figma structure — Identify frames, auto-layout, and component instances
- Map components — Match Figma component names/variants to IDS components
- Extract tokens — Convert Figma design values to IDS design token references
- Generate code — Produce clean, minimal React/TypeScript with proper IDS imports. Use the fewest components possible — check whether parent components already handle layout before adding
IressInline/IressStackwrappers. Never wrap a single child in a layout component. - Verify output — Check that all imports resolve, no raw HTML is used where IDS components exist, grid layouts use responsive
spanvalues, and no common anti-patterns are present (disabled buttons, slot attributes, redundant textStyle)
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 408 lines · 60 tokens per session scan A 70564ea20061
figma-to-ids is a skill published in the GitHub repository iress/design-system (1 stars, last pushed yesterday), licensed Apache-2.0. It adds 60 tokens to every session and 4,068 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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