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 parhamb/design-skills --skill ux-ai-automationgit clone --depth 1 https://github.com/parhamb/design-skillsWrote 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/parhamb/design-skills/ux-ai-automation)<a href="https://agentmods.dev/skills/parhamb/design-skills/ux-ai-automation"><img src="https://agentmods.dev/badge/skills/parhamb/design-skills/ux-ai-automation/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/parhamb/design-skills/ux-ai-automation"><img src="https://agentmods.dev/badge/skills/parhamb/design-skills/ux-ai-automation.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 | $0.00059 | $0.01072 |
| Opus 5.5 | $0.00024 | $0.00429 |
| Sonnet 5.5 | $0.00012 | $0.00214 |
| Haiku 4.5 | $0.00006 | $0.00107 |
Grade A, and why
ux-ai-automation 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 2mo 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI and Automation UX
AI features fail not because the model is bad, but because the experience around it is poorly designed. Users need to trust the AI, understand what it can and cannot do, stay in control, and recover gracefully when it is wrong.
Checklist
| Item | Guidance |
|---|---|
| AI assistant / chatbot | Clear entry point. Example prompts shown to start. Scope communicated upfront. |
| Smart recommendations | Explains why ("Because you liked X"). Includes a "Not interested" option. |
| AI-powered search | Supports natural language queries. Shows what the AI understood from the input. |
| Predictive input | Non-intrusive. Tap to accept, ignore to dismiss. Never auto-inserts without confirmation. |
| Auto-categorization | Shows the AI-assigned label and lets the user correct it inline. |
| AI-generated summaries | Clearly labeled as AI-generated. Links to the original source. |
| AI transparency | All AI-generated content is marked with a consistent icon or badge. |
| User control over AI | Per-feature opt-out in Settings. Not a single global "Disable AI" toggle. |
| AI error handling | Falls back gracefully when uncertain. Never exposes a raw model error to the user. |
| On-device AI | On-device processing is used for sensitive content (photos, notes, health data). |
| Feedback mechanism | Thumbs up / down on every AI output. Minimal friction to give feedback. |
| Automation and workflows | Preview of what the automation will do is shown before the user confirms execution. |
| Context-aware suggestions | Suggestions adapt to the user's current task, time of day, and usage history. |
| AI model update disclosure | Users are informed when the AI model powering a feature changes significantly. |
AI UX Principles
Explainability: Always answer "why is the AI showing me this?" — either proactively or available on demand. A recommendation with a visible reason is trusted. One without a reason is suspicious.
Graceful degradation: When confidence is low, the AI should say less, not guess more. "I'm not sure — here are 3 options" is better than one confident wrong answer.
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.
- 2mo ago First seen · 112 lines · 59 tokens per session scan A d2767d401587
ux-ai-automation is a skill published in the GitHub repository parhamb/design-skills (25 stars, last pushed 4mo ago), licensed MIT. It adds 59 tokens to every session and 1,072 once invoked, about $0.0002 per session on Opus 5.5. 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.
ux-ai-automation compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ux-ai-automationparhamb/design-skills | Skill | 25 | 4mo ago | MIT | A | 59 | Claude Code, Codex |
| planjeremylongshore/tons-of-skills-marketplace | Skill | 2.9k | yesterday | MIT | A | 144 | Claude Code |
| dstack-prototypingdstackai/dstack | Skill | 2.3k | yesterday | MPL-2.0 | A | 80 | Claude Code, Codex |
| senior-data-engineerbenchflow-ai/skillsbench | Skill | 1.9k | 3d ago | Apache-2.0 | A | 100 | Claude Code, Codex |
| llm-icon-finderdaymade/claude-code-skills | Skill | 1.5k | yesterday | MIT | A | 61 | Claude Code, Codex |
| enhance-promptgoogle-labs-code/stitch-skills | Skill | 8.7k | 2mo ago | Apache-2.0 | A | 41 | Claude Code |
| bim-classification-aidatadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction | Skill | 394 | 18d ago | MIT | A | 35 | Claude Code, Codex |