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 devinilabs/pro-skill --skill design-first-ui-promptinggit clone --depth 1 https://github.com/devinilabs/pro-skillWrote 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/devinilabs/pro-skill/design-first-ui-prompting)<a href="https://agentmods.dev/skills/devinilabs/pro-skill/design-first-ui-prompting"><img src="https://agentmods.dev/badge/skills/devinilabs/pro-skill/design-first-ui-prompting/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/devinilabs/pro-skill/design-first-ui-prompting"><img src="https://agentmods.dev/badge/skills/devinilabs/pro-skill/design-first-ui-prompting.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 | $0.00046 | $0.00819 |
| Opus 5 | $0.00023 | $0.00409 |
| Sonnet 5 | $0.00009 | $0.00164 |
| Haiku 4.5 | $0.00005 | $0.00082 |
Grade A, and why
design-first-ui-prompting 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 9d 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.
This is a copy
100% identical to design-first-ui-prompting — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design-First UI Prompting Skill
This skill is for design-first prompting: turn fuzzy ideas into a tight spec that produces consistent UI.
Core principle
Prompt like a design system, not a wish.
Prompt Structure (copy/paste)
Use this skeleton, then fill the blanks.
GOAL
- What are we making? (e.g., landing page hero / onboarding / dashboard / carousel slide)
- Who is it for? (persona)
- What’s the success criteria? (clarity, conversion, vibe)
FORMAT
- Size/aspect: (e.g., 1080x1350)
- Safe margins: (e.g., 90px)
LAYOUT (wireframe in words)
- Grid: (e.g., Swiss 6-col)
- Placement: (e.g., type-left / image-right)
- Hierarchy: H1 → subhead → body → CTA
TYPE SYSTEM
- Font vibe: (e.g., Söhne / Neue Haas / SF Pro)
- Weights: (H1 700, body 400)
- Leading: (tight for H1, readable for body)
- Tracking: (micro labels wider)
COLOR + MATERIAL
- Background: (hex or description)
- Text: (white/ivory/charcoal)
- One accent only: (cyan/lime/purple)
- Texture: (subtle grain, no plastic HDR)
IMAGERY / UI STYLE
- UI style: (minimal / glass / editorial / playful 3D)
- If photo: lighting + crop + texture rules
- If 3D: materials + lighting + softness
COPY (render EXACTLY)
- Line 1:
- Line 2:
- ...
CONSTRAINTS (change 1–2 things only)
- FONT: ___
- STYLE: ___
- MODE: ___
NEGATIVE PROMPT
- No logos, no watermarks
- No extra text beyond provided lines
- No gibberish typography
Rules that improve consistency
1) Lock one “system”, then iterate with variants
- First output: nail layout + hierarchy + copy.
- Variants: change ONE variable at a time:
- angle / crop
- accent color
- card arrangement
- background tone
2) Treat typography as fragile
If the model keeps misspelling:
- Use 2-pass workflow:
- Generate without text (reserve a clean text-safe area)
- Typeset in Figma
3) Use “constraints cards”
When you want the model to obey a style:
- Add a small “Constraints” panel with explicit values.
- It anchors the output like a mini style guide.
What ships with it
5 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.
- 9d ago First seen · 110 lines · 46 tokens per session scan A 5e3d4db0eb0e
design-first-ui-prompting is a skill published in the GitHub repository devinilabs/pro-skill (24 stars, last pushed 27d ago), licensed MIT. It adds 46 tokens to every session and 819 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to design-first-ui-prompting, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
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Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.
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Visual vocabulary, design terminology, and prompt engineering strategy for Stitch. Reference this when you need layout pattern names, aesthetic style terms, color structure formulas, or device guidelines.
ai-interaction-patterns
AI UX patterns — prompt UX, wayfinding, HITL, trust, disclosure, memory, generative UI.
stitch-ui-prompt-architect
Builds Stitch-ready prompts via two paths — Path A enhances vague ideas into polished prompts, Path B merges a Design Spec JSON + user request into a structured [Context] [Layout] [Components] prompt.
ai-feedback-loops
Design feedback mechanisms that help AI systems learn from users - thumbs up/down, preference ranking, corrections, and human-in-the-loop escalation. Use when: RLHF UX, user feedback for AI, thumbs up down design, AI correction flow, human in the loop, feedback signal design, AI improvement loops.
ai-product-design
Design or improve an AI-assisted feature, copilot, agent, recommendation, generation, or automation workflow with explicit capability boundaries, user control, recovery, trust, and evaluation. Trigger on "design this AI feature", "improve this copilot", or "plan this agent workflow". Do not default every AI product to…