agui-author
FeaturedAuthor live dashboard UI from an agent via the `emit_ui` MCP tool. Emit one of six allow-listed components (approval_card, choice_prompt, diff_summary, progress, metric, agent_card) with JSON props and it renders in any AG-UI client watching the fleet. Use when you want the operator to see a decision, a diff, or a status readout instead of scrolling terminal text. Arbitrary HTML/markup is refused.
Install
Quality Score: 89/100
Skill Content
Details
- Author
- awslabs
- Repository
- awslabs/cli-agent-orchestrator
- Created
- 1 years ago
- Last Updated
- today
- Language
- Python
- License
- Apache-2.0
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
agent-surface
Use when changing TUI, desktop, IDE extension, protocol-client, streaming chat UI, or approval dialogs. Use when the user mentions TUI, GUI, 前端, 桌面, protocol-client, Electron, VS Code.
ag-ui-a2ui-integration
Use when adding A2UI rendering to any AG-UI-supported framework or custom AG-UI application, scaffolding an AG-UI app that should render A2UI, adapting an AG-UI integration to emit A2UI surfaces, or wiring the AG-UI A2UI middleware/toolkit with a compatible renderer.
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.