agentic-ui-review

Reviews interfaces where an AI agent acts on the user's behalf (chat assistants that run tools, autonomous workflows, copilots that edit files or data) for the trust and control patterns those interfaces need - intent confirmation, approval gates scaled to risk, visible state and progress, tool-use transparency, honest uncertainty, interruptibility, reversibility, error recovery and accessible streaming output - against the published human-AI interaction guidelines, and produces severity-rated findings with concrete fixes. Use when designing or reviewing any UI that shows an agent planning, acting or asking for permission. Triggers on agentic UI, agent interface, AI assistant UX, copilot, approval flow, confirmation pattern, human in the loop, tool use transparency, agent progress, streaming state, uncertainty display, undo agent action, interrupt agent, autonomy level, trust calibration, AI explainability, generative UI.

Agentic interface review

Checks that a user can understand what an agent is about to do, stop it, approve the risky parts, see what happened, and recover when it goes wrong. The bar is calibrated trust: the user trusts the agent exactly as much as its reliability deserves, no more and no less.

Conversation copy and turn design belong to conversational-ux; accessibility mechanics to better-accessibility; dark patterns in consent or upsell steps to dark-pattern-review. This skill owns the lifecycle of an agent action as the user experiences it.

Inputs

The interface: screens, prototype, or the components that render agent plans, tool calls, results and errors.
What the agent can do: the tool list with each tool's blast radius (read, write, send, pay, delete) and reversibility.
The autonomy model: what runs without asking, what asks, who can change that.

Workflow

1. Map the action lifecycle

For each agent capability, trace the four moments the user meets it: before (intent stated, plan shown, permission asked), during (progress, current step, ability to pause or stop), after (what changed, where, how to undo), failure (what the agent knows, what it tried, what the user can do). Note where any moment is silent. Silence at "before" on a write or send action is the most common HIGH finding.

2. Check the pattern set

Read references/patterns.md for each pattern with the guideline it derives from and the test to apply. The set:

Intent echo — the agent restates the goal in its own words before acting on ambiguous requests (HAX G1, G2; PAIR "set expectations").
Plan preview — multi-step work is shown as steps before it runs, with the risky steps marked.
Approval scaled to risk — read-only actions run; reversible writes may run with visible undo; irreversible, external or costly actions ask first, and asking cannot be bypassed by wording. One approval covers one scope.
Live state — a persistent indicator of idle / thinking / acting / waiting-for-you, with the current step named, not a spinner alone.
Tool-use transparency — every tool call is inspectable: what was called, with what inputs, what came back, in a form the user can expand and cite (HAX G11 "make clear why the system did what it did").
Honest uncertainty — confidence is expressed where it changes the user's decision, in words the user can act on, never as a decorative percentage (HAX G10, PAIR "explainability + trust").
Interruptibility — stop is one action, always reachable, and stopping leaves a consistent state the interface describes.
Reversibility — completed actions list what changed with an undo or a path to reverse; when reversal is impossible the interface said so at approval time (HAX G8, G9; Apple HIG: let people correct and undo).
Error recovery — failures say what the agent knows, what it tried, and offer the user's options; they do not loop or silently retry writes (HAX G9 "support efficient correction").
Scope and memory disclosure — what the agent can see (files, data, history) and what it remembers are visible and editable (HAX G17, G18).
Accessible streaming — streamed output and status changes are announced to assistive technology (WCAG 2.2 SC 4.1.3 Status Messages, ARIA live regions), focus is not stolen, and generated content follows the same accessibility rules as authored content.
Generated UI governance — when the agent renders its own controls, they use the product's design system, carry the same confirmation rules, and cannot present a destructive action as primary.

3. Rate findings

HIGH: an irreversible, external or costly action can run without an explicit, scoped approval; the user cannot stop the agent; a failure leaves state the user cannot see; streamed status is invisible to assistive technology. MEDIUM: the pattern exists but is inconsistent (some tools transparent, others opaque; undo for some writes). LOW: clarity or placement issues with the mechanism present.

Name the component and the change. Prefer the cheaper fix: an approval step over a rewrite of the autonomy model; a status line over a redesign. When the fix changes what runs automatically, state the trade-off in throughput so the product owner decides knowingly.

5. Report

Moment is before / during / after / failure. Order by severity. End with Block when any HIGH remains, Approve otherwise. Report which capabilities were traced so unexamined tools are visible.

Before you finish

Mistake	Fix
Asking for approval on everything	Scale to blast radius and reversibility; constant prompts train blind approval
Treating a spinner as state	Name the step and the mode; make waiting-for-you distinct
Showing confidence as a number without a decision attached	Say what the user should do differently at that confidence
Reviewing only the chat pane	Trace tool calls, side effects and the undo path in the rest of the product
Assuming streamed text is accessible	Check live-region announcements and focus behaviour

Limitations

Guidelines cited are the 2026-08 versions; the field moves quickly. The skill reviews the interface contract, not model quality: an agent that asks correctly can still act wrongly, which evaluation skills and product analytics must catch.