debug-agent-threads

name: debug-agent-threads description: Inspection of thread history, memory, and organization-wide agent activity.

Debug Agent Threads

Skill for monitoring, debugging, and analyzing Lightdash AI agent conversations and configurations.

Purpose

Provides visibility into how agents interact with users. It allows for tracing context, identifying hallucinations, and auditing organization-wide AI settings and activity.

Tools

Wraps the following MCP tools from the lightdash-tools server:

• Conversations:
  • ldt__list_agent_threads
  • ldt__get_agent_thread
  • ldt__generate_agent_message
  • ldt__continue_agent_thread
• Admin & Monitoring:
  • ldt__list_admin_agents
  • ldt__list_admin_agent_threads
  • ldt__get_ai_organization_settings
  • ldt__update_ai_organization_settings

Safety Mode Compliance

• Read Tools: All list_ and get_ tools.
• Write-Safe Tools: generate_agent_message, continue_agent_thread.
• Write-Destructive Tools: update_ai_organization_settings.

Behavior

1. Memory Inspection:
   • Use ldt__get_agent_thread to retrieve the full message history of a specific conversation.
   • Analyze the history to see if the agent is correctly utilizing its memory or if it is exceeding context window limits.
2. Conversation Debugging:
   • Use ldt__generate_agent_message to test an agent's response to a specific prompt without persisting it to a thread if needed, or ldt__continue_agent_thread to simulate user interaction.
3. Organization Audit:
   • Use ldt__list_admin_agent_threads to monitor activity across the entire organization.
   • Check ldt__get_ai_organization_settings to verify that global safety and privacy settings are correctly configured.

Rules

• NEVER update organization-wide AI settings without explicit authorization.
• Use thread inspection to gather evidence before modifying an agent's persona or instructions.