Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add Adityaraj0421/naksha-studio/plugin install naksha-studioWrote 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/adityaraj0421/naksha-studio/design-score)<a href="https://agentmods.dev/commands/adityaraj0421/naksha-studio/design-score"><img src="https://agentmods.dev/badge/commands/adityaraj0421/naksha-studio/design-score.svg" alt="Measured on agentmods" 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 | $0.00022 | $0.02227 |
| Opus 5 | $0.00011 | $0.01113 |
| Sonnet 5 | $0.00004 | $0.00445 |
| Haiku 4.5 | $0.00002 | $0.00223 |
Grade A, and why
design-score 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 7d 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/design-score
Score a design across four dimensions: Accessibility (25pts), Usability (25pts), Visual Quality (25pts), Token Compliance (25pts). Total: 0–100.
Scoring Model
Read ${CLAUDE_PLUGIN_ROOT}/skills/design/references/ux-researcher.md — focus on "Nielsen's Heuristics" and "WCAG AA Checklist" sections before scoring.
Check for .naksha/project.json (search up to 3 directory levels). If found, read:
- v4 fields:
brand.primary,brand.secondary,brand.font, andtokenFormatfor Token Compliance scoring context. - v5 fields (if present — all optional):
constraints.grid→ use as the expected spacing unit. In Token Compliance, check all spacing values against this grid.constraints.min_contrast_ratio→ use as the required contrast ratio in Accessibility (overrides the default 4.5:1 if set higher).constraints.accessibility_target→"WCAG AAA"sets contrast floor to 7:1 for Accessibility scoring.constraints.breakpoints→ in Token Compliance, verify responsive breakpoints match these values.constraints.max_content_width→ flag if any container exceeds this.component_patterns→ in Token Compliance, check that components named in patterns use the recorded structure (padding, radius, border matches the description).browser_findings(5 most recent,mode: "inspect"entries) → prior design-score snapshots give baseline context. If a prior score exists, note delta: "Previously {N}/100 on {date}."
Dimension 1: Accessibility (0–25 pts)
Score each criterion with partial credit proportional to how many elements pass:
| Criterion | Max | Score |
|---|---|---|
| Primary text contrast ≥ 4.5:1; large text ≥ 3:1 (WCAG SC 1.4.3) | 6 | |
| UI component contrast ≥ 3:1 — buttons, inputs, focus rings (SC 1.4.11) | 4 | |
| All interactive elements have visible focus state (SC 2.4.7) | 4 | |
| Touch targets ≥ 44×44px on mobile interactive elements (SC 2.5.5) | 4 | |
| No information conveyed by color alone (SC 1.4.1) | 4 | |
| Form inputs have programmatic labels, not placeholder-only (SC 1.3.1) | 3 |
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.
- 7d ago First seen · 174 lines · 22 tokens per session scan A 938460bf7fae
design-score is a command published in the GitHub repository Adityaraj0421/naksha-studio (316 stars, last pushed 2mo ago), licensed MIT. It adds 22 tokens to every session and 2,227 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
brand
Generate a full editorial brand-guidelines book for any URL. 14 chapters covering brand essence/archetype, colour, typography, spacing, shape, iconography, motion, components, voice, accessibility, tokens, and how-to-use guidance. Print-ready, dark-mode toggle, hand-off-ready single HTML.
theme-swap
Recolour an extracted site's design around a new brand primary. OKLCH hue rotation preserves perceptual lightness — neutrals, type, spacing, and motion stay untouched. Side-by-side HTML preview + recoloured tokens (DTCG, Tailwind, shadcn, Figma).
dna
Place a design in the measured design space — nearest systems, per-axis percentiles, outliers.
extract
Extract the complete design language from a URL — DTCG tokens, Tailwind, Figma vars, motion, voice, components.
fidelity
Measure how faithfully a clone reproduces a site — pixel-diff plus motion-fidelity into one 0-100 score, a letter grade, a ranked correction plan, and a shareable card.
site
Crawl a whole site and synthesize ONE canonical design system across all pages — unified tokens, coverage map, consistency grade.