name: agent-ui description: Build specialized user interfaces for interacting with Agents triggers: [build agent ui, create tracing dashboard, implement agent front-end] tags: [ai] context_cost: low
agent-ui
Goal
Create specialized, responsive, and intuitive UI elements for tracing, visualizing, and interacting with AI agents.
Steps
- Component Design: Design UI components (e.g., using ShadCN) to visualize agent thoughts, tools, and actions.
- State Connection: Wire components to the backend agent state or streaming endpoints.
- UX Enhancement: Add micro-animations to indicate agent "thinking" or "executing" states.
- Verification: Verify that the UI flawlessly parses and renders unstructured or partially streamed markdown / JSON.
Security & Guardrails
1. Skill Security
- XSS Prevention: Vigorously encode all agent output before rendering it in the UI, as LLM responses can contain malicious payloads.
- Markdown Sandbox: Ensure the markdown parser disables executable scripts or insecure HTML tags.
2. System Integration Security
- Access Control: Hide administrative agent actions (e.g., "approve PR", "deploy") behind rigorous user authentication/RBAC.
- Secret Masking: The UI must automatically detect and mask sensitive data (like API keys) that the agent might accidentally log or stream.
3. LLM & Agent Guardrails
- Hallucinated Actions: The UI must not blindly execute client-side functions suggested by the LLM without human confirmation.
- Status Transparency: Ensure the UI clearly distinguishes between "Agent generated this" and "Human authored this" for clear accountability.