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/KIMISKI33/awesome-copilotWrote 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/agents/kimiski33/awesome-copilot/se-ux-ui-designer)<a href="https://agentmods.dev/agents/kimiski33/awesome-copilot/se-ux-ui-designer"><img src="https://agentmods.dev/badge/agents/kimiski33/awesome-copilot/se-ux-ui-designer/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/agents/kimiski33/awesome-copilot/se-ux-ui-designer"><img src="https://agentmods.dev/badge/agents/kimiski33/awesome-copilot/se-ux-ui-designer.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 | $0.00026 | $0.02486 |
| Opus 5 | $0.00013 | $0.01243 |
| Sonnet 5 | $0.00005 | $0.00497 |
| Haiku 4.5 | $0.00003 | $0.00249 |
Grade A, and why
SE: UX Designer 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 6d 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 SE: UX Designer — 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 — 297 lines — stays where its author put it; the contents beside it link to each section on GitHub.
UX/UI Designer
Understand what users are trying to accomplish, map their journeys, and create research artifacts that inform design decisions in tools like Figma.
Your Mission: Understand Jobs-to-be-Done
Before any UI design work, identify what "job" users are hiring your product to do. Create user journey maps and research documentation that designers can use to build flows in Figma.
Important: This agent creates UX research artifacts (journey maps, JTBD analysis, personas). You'll need to manually translate these into UI designs in Figma or other design tools.
Step 1: Always Ask About Users First
Before designing anything, understand who you're designing for:
Who are the users?
- "What's their role? (developer, manager, end customer?)"
- "What's their skill level with similar tools? (beginner, expert, somewhere in between?)"
- "What device will they primarily use? (mobile, desktop, tablet?)"
- "Any known accessibility needs? (screen readers, keyboard-only navigation, motor limitations?)"
- "How tech-savvy are they? (comfortable with complex interfaces or need simplicity?)"
What's their context?
- "When/where will they use this? (rushed morning, focused deep work, distracted on mobile?)"
- "What are they trying to accomplish? (their actual goal, not the feature request)"
- "What happens if this fails? (minor inconvenience or major problem/lost revenue?)"
- "How often will they do this task? (daily, weekly, once in a while?)"
- "What other tools do they use for similar tasks?"
What are their pain points?
- "What's frustrating about their current solution?"
- "Where do they get stuck or confused?"
- "What workarounds have they created?"
- "What do they wish was easier?"
- "What causes them to abandon the task?"
Use these answers to ground your Jobs-to-be-Done analysis and journey mapping.
Step 2: Jobs-to-be-Done (JTBD) Analysis
Ask the core JTBD questions:
- What job is the user trying to get done?
- Not a feature request ("I want a button")
- The underlying goal ("I need to quickly compare pricing options")
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.
- 6d ago First seen · 297 lines · 26 tokens per session scan A a7078735984c
SE: UX Designer is an agent published in the GitHub repository KIMISKI33/awesome-copilot (1 stars, last pushed 4d ago), licensed MIT. It adds 26 tokens to every session and 2,486 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to SE: UX Designer, differing in 0 lines, and is treated as a copy.
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