Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/freema/mcp-design-system-extractorWrote 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/commands/freema/mcp-design-system-extractor/theme)<a href="https://agentmods.dev/commands/freema/mcp-design-system-extractor/theme"><img src="https://agentmods.dev/badge/commands/freema/mcp-design-system-extractor/theme/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/commands/freema/mcp-design-system-extractor/theme"><img src="https://agentmods.dev/badge/commands/freema/mcp-design-system-extractor/theme.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 | $0.00011 | $0.00122 |
| Opus 5.5 | $0.00004 | $0.00049 |
| Sonnet 5.5 | $0.00002 | $0.00024 |
| Haiku 4.5 | $0.00001 | $0.00012 |
Grade A, and why
theme 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 1mo 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.
What it actually says
/design:theme
Extract design tokens and theme information from the design system.
Usage
/design:theme # Full theme
/design:theme <section> # Specific section
Examples
/design:theme
/design:theme colors
/design:theme spacing
/design:theme typography
What Happens
Calls get_theme_info to extract CSS custom properties and design tokens including colors, spacing, typography, and breakpoints.
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.
- 1mo ago First seen · 29 lines · 11 tokens per session scan A 7e99dc923053
theme is a command published in the GitHub repository freema/mcp-design-system-extractor (70 stars, last pushed 1mo ago), licensed MIT. It adds 11 tokens to every session and 122 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-08-30.
Other commands, from other repositories
verify
Fidelity check — rebuild a page from the extracted tokens, pixel-diff it against the live site, and score how faithfully the tokens capture the design.
design-tutorial
Interactive guided tour of Naksha — learn commands through real exercises, discover workflows, and get oriented in under 10 minutes.
ux-audit
Audit a Figma file against a design brief — checks page structure, frame naming, sizes, styles, components, and content compliance.
critique-screen
Run all seven visual critiques on a screen and output a prioritised fix list.
critique-ux
Run a focused UX critique on a screen — affordances, information density, and hierarchy — and output a prioritised fix list.
design-onboarding
Design a first-run experience end to end — activation path, progressive disclosure, and time to first value.