agent-ui

Goal

Create specialized, responsive, and intuitive UI elements for tracing, visualizing, and interacting with AI agents.

Steps

1. Component Design: Design UI components (e.g., using ShadCN) to visualize agent thoughts, tools, and actions.
2. State Connection: Wire components to the backend agent state or streaming endpoints.
3. UX Enhancement: Add micro-animations to indicate agent "thinking" or "executing" states.
4. 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.