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 varunk130/ai-ux-skill-library --skill ai-agent-uxgit clone --depth 1 https://github.com/varunk130/ai-ux-skill-libraryWrote 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/varunk130/ai-ux-skill-library/ai-agent-ux)<a href="https://agentmods.dev/skills/varunk130/ai-ux-skill-library/ai-agent-ux"><img src="https://agentmods.dev/badge/skills/varunk130/ai-ux-skill-library/ai-agent-ux/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/varunk130/ai-ux-skill-library/ai-agent-ux"><img src="https://agentmods.dev/badge/skills/varunk130/ai-ux-skill-library/ai-agent-ux.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 | $0.00065 | $0.01966 |
| Opus 5 | $0.00032 | $0.00983 |
| Sonnet 5 | $0.00013 | $0.00393 |
| Haiku 4.5 | $0.00006 | $0.00197 |
Grade A, and why
ai-agent-ux 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 12d 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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Agent UX
Design experiences for AI that doesn't just suggest - it acts. Booking flights, sending emails, executing code, making purchases. The AUTONOMY framework ensures users stay in control while AI operates at machine speed.
Core Principle
Agentic AI inverts the traditional UX model. In classical UX, users take actions and the system responds. In agentic UX, the system takes actions and users supervise. This requires an entirely new design vocabulary: previews instead of forms, audit trails instead of history, interrupts instead of navigation.
The AUTONOMY Framework
| Letter | Principle | Design Question |
|---|---|---|
| A | Action Preview | Can the user see exactly what the agent will do before it does it? |
| U | User Override | Can the user stop, modify, or redirect the agent at any point during execution? |
| T | Tiered Authority | Does the agent's freedom scale appropriately with risk level? |
| O | Observable State | Can the user see what the agent is doing right now, in real time? |
| N | Narrated Reasoning | Does the agent explain why it chose this action over alternatives? |
| O | Outcome Verification | Can the user verify that the action completed correctly? |
| M | Memory of Actions | Is there a complete, searchable log of everything the agent did? |
| Y | Yield to Humans | Does the agent know when to stop and ask for help? |
The Autonomy Dial
Not all actions require the same level of human oversight. Design a graduated control system:
| Level | Name | Agent Behavior | User Involvement | Example |
|---|---|---|---|---|
| 1 | Suggest | Recommends action, takes none | User must initiate | "I recommend replying with: [draft]. Send?" |
| 2 | Draft & Wait | Prepares the action, pauses for approval | User reviews and approves | Agent drafts email, shows preview, waits for "Send" |
| 3 | Act & Notify | Executes immediately, sends notification | User reviews after the fact | Agent files expense report, sends summary |
| 4 | Act Silently | Executes without notification | User can check audit log | Agent auto-categorizes emails |
| 5 | Full Autonomy | Executes complex multi-step tasks independently | User sets goals, agent reports outcomes | Agent manages a full sales outreach sequence |
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.
- 12d ago First seen · 180 lines · 65 tokens per session scan A 6ea0a6083152
ai-agent-ux is a skill published in the GitHub repository varunk130/ai-ux-skill-library (3 stars, last pushed 1mo ago), licensed MIT. It adds 65 tokens to every session and 1,966 once invoked, about $0.0003 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 2026-08-31.
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