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Monitoring User Frustration

Use the frustration tools to identify and investigate unhappy users. Workflow:
  1. Start with moda_get_overview to see the frustration rate
  2. Use moda_get_frustrations to get specific frustrated conversations with evidence
  3. Drill into a conversation with moda_get_conversation_context to see the full context
Example prompt for Claude Code:
“Check if any users were frustrated in the last 7 days and show me the details”

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Investigating Tool Failures

Identify which tools are failing and why. Workflow:
  1. Call moda_get_tool_failures to see which tools have the most failures
  2. Pick a tool and call moda_get_tool_failure_detail to see error subtypes and examples
  3. Use the inline conversation context in each example to understand the failure scenario
Example prompt for Claude Code:
“Which tools are failing the most? Show me examples of the top failing tool”

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Exploring Conversation Clusters

Understand what topics your users are discussing. Workflow:
  1. Call moda_get_clusters to see root-level topic categories
  2. Drill into a category by passing its node_id as parent_id
  3. Use moda_get_cluster_conversations to see specific conversations in a cluster
Example prompt for Claude Code:
“What are the main topics users are asking about? Drill into the biggest cluster”

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Searching Conversations

Find specific conversations by content, user, or time range. Workflow:
  1. Use moda_search_conversations with a search term for full-text search
  2. Filter by environment to focus on production vs. development
  3. Use moda_get_conversation_context to read specific conversations
Example prompt for Claude Code:
“Find all production conversations mentioning ‘timeout errors’ from the last 24 hours”

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Finding Conversations by World State

The agent’s world state captures what it has learned in a conversation — structured slots plus a durable per-user profile. Search across it with keywords to surface conversations that involve a particular fact, goal, or user attribute, and combine it with --outcome to focus on good or bad runs. 
# Positive (successful, non-frustrated) conversations whose world state mentions "enterprise"
moda conversations --world-state="enterprise" --outcome=positive

# AND multiple keywords, and attach the matched world state to each result
moda conversations --world-state="refund,billing" --include-world-state

# Drill into one conversation's slots, open threads, and how they were learned
moda world-state <conversation_id>
Keyword matching is a case-insensitive substring over the full world-state content (segment slots and carried-in durable profile), so you don’t need to know the exact slot key — useful while slot naming is still evolving. Example prompt for Claude Code:
“Find positive conversations where the user is on an enterprise plan, then show me the world state for the first one”