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 agentmods add skills/educlopez/ui-craft/craftnpx skills add educlopez/ui-craft --skill craftgit clone --depth 1 https://github.com/educlopez/ui-craftWrote 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/educlopez/ui-craft/craft)<a href="https://agentmods.dev/skills/educlopez/ui-craft/craft"><img src="https://agentmods.dev/badge/skills/educlopez/ui-craft/craft.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 | $0.00089 | $0.01446 |
| Opus 5 | $0.00044 | $0.00723 |
| Sonnet 5 | $0.00018 | $0.00289 |
| Haiku 4.5 | $0.00009 | $0.00145 |
Grade A, and why
craft 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 4d 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context: this sub-skill is one lens of the broader ui-craft skill. If the ui-craft skill is also installed, read its SKILL.md first for Discovery + Anti-Slop + Craft Test, then apply the specific lens below.
Load the ui-craft skill. This command BUILDS — it ends with working code that passes the recipe's acceptance bar.
Recipes available: dashboard → references/recipe-dashboard.md · landing → references/recipe-landing.md · auth (sign-in/sign-up) → references/recipe-auth.md. If $ARGUMENTS names a surface with no recipe yet (settings, docs, e-commerce), say so and fall back to standard Build mode with the closest references — do not improvise a fake recipe.
Step 0 — Load spec (if present)
Before anything else: if .ui-craft/spec.md exists and contains a ## Surface: <name> section whose name matches $ARGUMENTS, load that section now. Its chosen composition, component inventory, state lattice, and acceptance bar take precedence over the recipe defaults for all downstream steps. Note which acceptance bar items came from the spec vs. recipe defaults.
Step 1 — Inputs
Run Stack Detection + Discovery Step 1 (existing tokens, .ui-craft/brief.md).
Load references/craft-intent.md.
Ask the recipe's Step 0 questions in ONE compact prompt, pre-filling anything $ARGUMENTS or the brief already answers. If the user declines, says "you decide", or has answered before in this session: apply the recipe defaults silently and say which were applied. Never ask twice; never block.
Set DESIGN_VARIANCE from craft-intent defaults for this surface type unless the user or brief specifies otherwise.
Step 2 — Craft Read + lock the plan
Output the Craft Read (one line, craft-intent §1) before any code. Include: surface kind, audience, product vs marketing language, theme/accent, variance, signature bet.
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.
- 4d ago First seen · 75 lines · 89 tokens per session scan A a6db8454a848
craft is a skill published in the GitHub repository educlopez/ui-craft (310 stars, last pushed today), licensed MIT. It adds 89 tokens to every session and 1,446 once invoked, about $0.0004 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 skills, from other repositories
software-in-worten
Übersetzt zwischen Benutzeroberfläche und Text — in beide Richtungen. Aus einer beschriebenen Oberfläche wird ein Skill; aus einem Skill wird eine Oberfläche. Nutzen, wenn eine Anwendung entworfen wird und der Ablauf noch unklar ist, wenn ein bestehendes Werkzeug als Skill verfügbar gemacht werden soll, wenn…
gradio-themes
Build and customise Gradio themes. Use when creating, editing, or publishing Python-based Gradio themes that control colours, typography, spacing, shadows, and dark mode.
visual-plan
Turn ordinary text plans into rich interactive visual plans with diagrams, file maps, annotated code, open questions, and UI/prototype review when useful.
shadcn-ui-flutter
A comprehensive Flutter UI library inspired by shadcn/ui. Provides high-quality, customizable, and accessible components including Buttons, Cards, Forms, and more. Use this skill when building Flutter UIs, implementing design systems, or needing specific component usage examples.
accessibility
Audit and improve web accessibility following WCAG 2.2 guidelines. Use when asked to "improve accessibility", "a11y audit", "WCAG compliance", "screen reader support", "keyboard navigation", or "make accessible".
nano-banana
Generate professional presentation slides and high-quality illustrations using Gemini image generation API (Nano Banana 2), with interactive browser-based review and iterative editing. Full workflow: content planning conversation → slidesplan.json → batch image generation → review with feedback → targeted slide…