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.
npx skills add mgiovani/cc-arsenal --skill review-designgit clone --depth 1 https://github.com/mgiovani/cc-arsenalWrote 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/mgiovani/cc-arsenal/review-design)<a href="https://agentmods.dev/skills/mgiovani/cc-arsenal/review-design"><img src="https://agentmods.dev/badge/skills/mgiovani/cc-arsenal/review-design/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/mgiovani/cc-arsenal/review-design"><img src="https://agentmods.dev/badge/skills/mgiovani/cc-arsenal/review-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00198 | $0.03238 |
| Opus 5 | $0.00099 | $0.01619 |
| Sonnet 5 | $0.00040 | $0.00648 |
| Haiku 4.5 | $0.00020 | $0.00324 |
Grade A, and why
review-design 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 10d 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 — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Review
Comprehensive UX/UI/design quality analysis across 8 audit dimensions, each mapped to authoritative standards. This skill performs analysis only - it identifies design issues, explains findings against a cited criterion, and suggests fix approaches without making code changes.
It supports two input modes:
- Live mode: audits a running URL via the
agent-browserCLI (screenshots + DOM/accessibility snapshot). - Static mode: audits a codebase (CSS/components/design tokens) via Grep.
When both a URL and a codebase target are supplied, it runs both and emits two separate reports.
Audit Taxonomy (8 Dimensions)
| # | Dimension | Key Standards |
|---|---|---|
| 1 | Visual Hierarchy & Layout | NN/g, Refactoring UI, Laws of UX, MD3 8pt grid |
| 2 | Typography | Butterick, Refactoring UI, MD3, Apple HIG |
| 3 | Color & Theming (incl. Dark Mode) | MD3 color roles, 60-30-10, WCAG 1.4.1/1.4.3 |
| 4 | Depth & Elevation (Shadows) | MD3 elevation, Refactoring UI, Josh Comeau |
| 5 | Components & Affordance (Buttons/Icons) | MD3 buttons/icons, Apple HIG, NN/g |
| 6 | Feedback & States | NN/g visibility-of-status, MD3 state layers |
| 7 | Motion & Microinteractions | NN/g animation, Laws of UX (Doherty), MD3 motion |
| 8 | Accessibility (cross-cutting) | WCAG 2.2 AA |
Measurable criteria for dimensions 1–4 are in references/criteria-foundations.md; dimensions 5–8 are in references/criteria-interaction.md.
Anti-Hallucination Guidelines
CRITICAL: Design reviews must be based on ACTUAL evidence, never assumptions:
- Observe before claiming - Never report an issue without reading the code (static) or viewing the screenshot/snapshot (live)
- Evidence-based findings - Every finding cites a file path + line number (static) OR a screenshot region + DOM ref (live)
- Cite a criterion - Every finding maps to a criterion ID and an authoritative citation (WCAG SC, MD3 spec, etc.)
- Measure, don't estimate - Report actual values (contrast ratio, px size, ms duration), not guesses. In static mode there is no rendered page to sample from: compute the WCAG relative-luminance contrast ratio directly from the two hex/rgb values found in the CSS/tokens (formula in references/agent-prompts.md); never eyeball a ratio
- Applicable-only scoring - Only score dimensions that apply to the target; never penalize what cannot be observed
- State what was NOT checked - Every report ends with an explicit coverage gap section
- No invented standards - Only reference real WCAG SCs, MD3 specs, and HIG guidance
What ships with it
10 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.
- evals/evals.json 3.8 KB
- evals/fixtures/clean-fixture.css 716 B
- evals/fixtures/clean-fixture.html 337 B
- evals/fixtures/low-contrast-fixture.css 619 B
- evals/fixtures/low-contrast-fixture.html 323 B
- evals/trigger-eval.json 2.1 KB
- references/agent-prompts.md 12 KB
- references/criteria-foundations.md 8.1 KB
- references/criteria-interaction.md 7.8 KB
- references/report-template.md 5.7 KB
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.
- 10d ago First seen · 257 lines · 198 tokens per session scan A 92a2aa7e4a86
review-design is a skill published in the GitHub repository mgiovani/cc-arsenal (8 stars, last pushed yesterday), licensed MIT. It adds 198 tokens to every session and 3,238 once invoked, about $0.0010 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.
Other skills, from other repositories
cli-anything-photoshop
A command-line tool that controls Adobe Photoshop through Windows automation. It can work with Photoshop documents, layers, selections, text, image adjustments, and exports.
extract-design-system
Extract design primitives from a public website and generate starter token files for your project.
double-diamond
A four-stage design method for understanding a problem, defining it clearly, exploring possible solutions, and choosing one to deliver.
nous-branding
Generate images and content consistent with the Nous Research brand identity. Use when creating visuals in the Nous / Theia / Hermes ecosystem: a "cyber-classical" style blending neo-classical statuary, cyberpunk/industrial grunge, and retro anime illustration. Covers official brand color palette, typography…
figma-use
Control Figma via CLI — create shapes, frames, text, components, set styles, layout, variables, export images. Use when asked to create/modify Figma designs or automate design tasks.
awesome-design-md
Create a DESIGN.md style baseline BEFORE building UI. Use FIRST when no design draft exists — installs a proven visual style, then invoke frontend-design to implement. For borrowing a known product style, getting consistent typography/colors/spacing, or needing a fast visual starting point.