{ "_meta": { "schema_version": 15, "generated_at": "2026-10-06T18:28:24.645+00:00", "source": "langley/langley/llm_analytics/taxonomy_catalog.py", "category": "Agent Analytics" }, "events": [ { "event_type": "[Agent] User Message", "description": "Fired when a user sends a message to an AI agent. Captures session/trace/turn context, message content (via $llm_message chunking), implicit feedback signals (regeneration, edit), and file attachments. The entry point for user-initiated AI interactions.", "properties": [ { "name": "[Agent] Session ID", "type": "string", "description": "Unique session identifier. All events in one conversation share the same session ID.", "is_required": true }, { "name": "[Agent] Trace ID", "type": "string", "description": "Identifies one user-message-to-AI-response cycle within a session." }, { "name": "[Agent] Turn ID", "type": "number", "description": "Monotonically increasing counter for event ordering within a session." }, { "name": "[Agent] Agent ID", "type": "string", "description": "Identifies which AI agent handled the interaction (e.g., 'support-bot', 'houston')." }, { "name": "[Agent] Parent Agent ID", "type": "string", "description": "For multi-agent orchestration: the agent that delegated to this agent." }, { "name": "[Agent] Customer Org ID", "type": "string", "description": "Organization ID for multi-tenant platforms. Enables account-level group analytics." }, { "name": "[Agent] Agent Version", "type": "string", "description": "Agent code version (e.g., 'v4.2'). Enables version-over-version quality comparison." }, { "name": "[Agent] Agent Description", "type": "string", "description": "Human-readable description of the agent's purpose (e.g., 'Handles user chat requests via OpenAI GPT-4o'). Enables observability-driven agent registry from event streams." }, { "name": "[Agent] Context", "type": "string", "description": "Serialized JSON dict of arbitrary segmentation dimensions (experiment_variant, surface, feature_flag, prompt_revision, etc.)." }, { "name": "[Agent] Env", "type": "string", "description": "Deployment environment: 'production', 'staging', or 'dev'." }, { "name": "[Agent] Tags", "type": "string", "description": "User-defined tags for filtering/segmentation. Serialized JSON array of strings." }, { "name": "[Agent] Git SHA", "type": "string", "description": "Git commit SHA of the deployed agent code. Auto-captured from environment or git CLI." }, { "name": "[Agent] Git Ref", "type": "string", "description": "Git branch or tag name (e.g., 'main', 'v1.2.3'). Auto-captured from environment or git CLI." }, { "name": "[Agent] Git Repo", "type": "string", "description": "Git repository URL. Auto-captured from environment or git CLI." }, { "name": "[Agent] SDK Version", "type": "string", "description": "Version of the amplitude-ai SDK that produced this event.", "is_required": true }, { "name": "[Agent] Ingestion Path", "type": "string", "description": "How the events were written: 'sdk', 'http_forwarder', 'warehouse_import', or 'otlp'." }, { "name": "[Agent] Source", "type": "string", "description": "Writer that produced the events, for example 'node-sdk', 'python-sdk', 'sierra', 'warehouse-sql', or 'databricks'." }, { "name": "[Agent] Content Mode", "type": "string", "description": "Privacy posture: 'full', 'metadata_only', or 'customer_enriched'. Stamped even when message text is omitted." }, { "name": "[Agent] Runtime", "type": "string", "description": "SDK runtime: 'python' or 'node'.", "is_required": true }, { "name": "[Agent] Message ID", "type": "string", "description": "Unique identifier for this message event (UUID). Used to link scores and tool calls back to specific messages.", "is_required": true }, { "name": "[Agent] Component Type", "type": "string", "description": "Type of component that produced this event: 'user_input', 'llm', 'tool', 'embedding'.", "is_required": true }, { "name": "[Agent] Locale", "type": "string", "description": "User locale (e.g., 'en-US')." }, { "name": "[Amplitude] Session Replay ID", "type": "string", "description": "Links to Amplitude Session Replay (format: device_id/session_id). Enables one-click navigation from AI session to browser replay." }, { "name": "[Agent] Is Regeneration", "type": "boolean", "description": "Whether the user requested the AI regenerate a previous response." }, { "name": "[Agent] Is Edit", "type": "boolean", "description": "Whether the user edited a previous message and resubmitted." }, { "name": "[Agent] Edited Message ID", "type": "string", "description": "The message_id of the original message that was edited (links the edit to the original)." }, { "name": "[Agent] Has Attachments", "type": "boolean", "description": "Whether this message includes file attachments (uploads, images, etc.)." }, { "name": "[Agent] Attachment Types", "type": "string", "description": "Distinct attachment types (e.g., 'pdf', 'image', 'csv'). Serialized JSON array.", "is_array_type": true }, { "name": "[Agent] Attachment Count", "type": "number", "description": "Number of file attachments included with this message." }, { "name": "[Agent] Total Attachment Size Bytes", "type": "number", "description": "Total size of all attachments in bytes." }, { "name": "[Agent] Attachments", "type": "string", "description": "Serialized JSON array of attachment metadata (type, name, size_bytes, mime_type). Only metadata, never file content." }, { "name": "[Agent] Message Labels", "type": "string", "description": "Serialized JSON array of MessageLabel objects (key-value pairs with optional confidence). Used for routing tags, classifier output, business context." }, { "name": "[Agent] Message Source", "type": "string", "description": "Origin of the user message: 'user' for real end-user input, 'agent' for inter-agent delegation (parent agent sending instructions to a child agent). Automatically set by provider wrappers based on parent_agent_id context." } ] }, { "event_type": "[Agent] AI Response", "description": "Fired when an AI agent generates a response. Captures model, provider, latency, TTFB, token breakdowns (input/output/reasoning/cache), cache-aware cost, finish reason, reasoning content, system prompt, model configuration, copy signal, and model tier. The primary event for LLM performance and cost analytics.", "properties": [ { "name": "[Agent] Session ID", "type": "string", "description": "Unique session identifier. All events in one conversation share the same session ID.", "is_required": true }, { "name": "[Agent] Trace ID", "type": "string", "description": "Identifies one user-message-to-AI-response cycle within a session." }, { "name": "[Agent] Turn ID", "type": "number", "description": "Monotonically increasing counter for event ordering within a session." }, { "name": "[Agent] Agent ID", "type": "string", "description": "Identifies which AI agent handled the interaction (e.g., 'support-bot', 'houston')." }, { "name": "[Agent] Parent Agent ID", "type": "string", "description": "For multi-agent orchestration: the agent that delegated to this agent." }, { "name": "[Agent] Customer Org ID", "type": "string", "description": "Organization ID for multi-tenant platforms. Enables account-level group analytics." }, { "name": "[Agent] Agent Version", "type": "string", "description": "Agent code version (e.g., 'v4.2'). Enables version-over-version quality comparison." }, { "name": "[Agent] Agent Description", "type": "string", "description": "Human-readable description of the agent's purpose (e.g., 'Handles user chat requests via OpenAI GPT-4o'). Enables observability-driven agent registry from event streams." }, { "name": "[Agent] Context", "type": "string", "description": "Serialized JSON dict of arbitrary segmentation dimensions (experiment_variant, surface, feature_flag, prompt_revision, etc.)." }, { "name": "[Agent] Env", "type": "string", "description": "Deployment environment: 'production', 'staging', or 'dev'." }, { "name": "[Agent] Tags", "type": "string", "description": "User-defined tags for filtering/segmentation. Serialized JSON array of strings." }, { "name": "[Agent] Git SHA", "type": "string", "description": "Git commit SHA of the deployed agent code. Auto-captured from environment or git CLI." }, { "name": "[Agent] Git Ref", "type": "string", "description": "Git branch or tag name (e.g., 'main', 'v1.2.3'). Auto-captured from environment or git CLI." }, { "name": "[Agent] Git Repo", "type": "string", "description": "Git repository URL. Auto-captured from environment or git CLI." }, { "name": "[Agent] SDK Version", "type": "string", "description": "Version of the amplitude-ai SDK that produced this event.", "is_required": true }, { "name": "[Agent] Ingestion Path", "type": "string", "description": "How the events were written: 'sdk', 'http_forwarder', 'warehouse_import', or 'otlp'." }, { "name": "[Agent] Source", "type": "string", "description": "Writer that produced the events, for example 'node-sdk', 'python-sdk', 'sierra', 'warehouse-sql', or 'databricks'." }, { "name": "[Agent] Content Mode", "type": "string", "description": "Privacy posture: 'full', 'metadata_only', or 'customer_enriched'. Stamped even when message text is omitted." }, { "name": "[Agent] Runtime", "type": "string", "description": "SDK runtime: 'python' or 'node'.", "is_required": true }, { "name": "[Agent] Message ID", "type": "string", "description": "Unique identifier for this message event (UUID). Used to link scores and tool calls back to specific messages.", "is_required": true }, { "name": "[Agent] Component Type", "type": "string", "description": "Type of component that produced this event: 'user_input', 'llm', 'tool', 'embedding'.", "is_required": true }, { "name": "[Agent] Stack Trace", "type": "string", "description": "Error stack trace when Is Error is true and captureStackTrace is enabled. Opt-in only — may contain file paths." }, { "name": "[Agent] Error Source", "type": "string", "description": "Origin of the error: 'provider' (LLM API error), 'tool' (tool execution failure), 'agent' (agent logic error)." }, { "name": "[Agent] Model Name", "type": "string", "description": "LLM model identifier (e.g., 'gpt-4o', 'claude-sonnet-4-20250514').", "is_required": true }, { "name": "[Agent] Provider", "type": "string", "description": "LLM provider name (e.g., 'openai', 'anthropic', 'google', 'mistral', 'bedrock').", "is_required": true }, { "name": "[Agent] Provider Request ID", "type": "string", "description": "Provider-owned inference identifier. On AI Response this is captured from the provider response; on Score it is present only when explicitly supplied." }, { "name": "[Agent] Latency Ms", "type": "number", "description": "Total wall-clock latency in milliseconds for this operation.", "is_required": true }, { "name": "[Agent] Is Error", "type": "boolean", "description": "Whether this event represents an error condition.", "is_required": true }, { "name": "[Agent] Error Message", "type": "string", "description": "Error message text when Is Error is true." }, { "name": "[Agent] Error Type", "type": "string", "description": "Exception class name when Is Error is true (e.g., 'ValidationError', 'TimeoutError'). Distinct from Error Message so downstream tooling can group failures by type without parsing the message." }, { "name": "[Agent] Locale", "type": "string", "description": "User locale (e.g., 'en-US')." }, { "name": "[Agent] Span Kind", "type": "string", "description": "Classification of the span type for OTEL bridge compatibility." }, { "name": "[Amplitude] Session Replay ID", "type": "string", "description": "Links to Amplitude Session Replay (format: device_id/session_id). Enables one-click navigation from AI session to browser replay." }, { "name": "[Agent] TTFB Ms", "type": "number", "description": "Time to first byte/token in milliseconds. Measures perceived responsiveness for streaming." }, { "name": "[Agent] Input Tokens", "type": "number", "description": "Number of input/prompt tokens consumed by this LLM call." }, { "name": "[Agent] Output Tokens", "type": "number", "description": "Number of output/completion tokens generated by this LLM call." }, { "name": "[Agent] Total Tokens", "type": "number", "description": "Total tokens consumed (input + output)." }, { "name": "[Agent] Reasoning Tokens", "type": "number", "description": "Tokens consumed by reasoning/thinking (o1, o3, extended thinking models)." }, { "name": "[Agent] Cache Read Tokens", "type": "number", "description": "Input tokens served from the provider's prompt cache (cheaper rate). Used for cache-aware cost calculation." }, { "name": "[Agent] Cache Creation Tokens", "type": "number", "description": "Input tokens that created new prompt cache entries." }, { "name": "[Agent] Cost USD", "type": "number", "description": "Estimated cost in USD for this LLM call. Cache-aware when cache token counts are provided." }, { "name": "[Agent] Finish Reason", "type": "string", "description": "Why the model stopped generating: 'stop', 'end_turn', 'tool_use', 'length', 'content_filter', etc." }, { "name": "[Agent] Tool Calls", "type": "string", "description": "Serialized JSON array of tool call requests made by the AI in this response." }, { "name": "[Agent] Has Reasoning", "type": "boolean", "description": "Whether the AI response included reasoning/thinking content." }, { "name": "[Agent] Reasoning Content", "type": "string", "description": "The AI's reasoning/thinking content (when available and content_mode permits)." }, { "name": "[Agent] System Prompt", "type": "string", "description": "The system prompt used for this LLM call (when content_mode permits). Chunked for long prompts." }, { "name": "[Agent] System Prompt Length", "type": "number", "description": "Character length of the system prompt." }, { "name": "[Agent] Tool Definitions", "type": "string", "description": "Normalized JSON array of tool definitions sent to the LLM (when content_mode permits). Each entry contains name, description, and parameters schema." }, { "name": "[Agent] Tool Definitions Count", "type": "number", "description": "Number of tool definitions in the LLM request." }, { "name": "[Agent] Tool Definitions Hash", "type": "string", "description": "Stable SHA-256 hash of the normalized tool definitions. Always present regardless of content_mode; enables toolset change detection without exposing schemas." }, { "name": "[Agent] Temperature", "type": "number", "description": "Temperature parameter used for this LLM call." }, { "name": "[Agent] Max Output Tokens", "type": "number", "description": "Maximum output tokens configured for this LLM call." }, { "name": "[Agent] Top P", "type": "number", "description": "Top-p (nucleus sampling) parameter used for this LLM call." }, { "name": "[Agent] Is Streaming", "type": "boolean", "description": "Whether this response was generated via streaming." }, { "name": "[Agent] Prompt ID", "type": "string", "description": "Identifier for the prompt template or version used." }, { "name": "[Agent] Was Copied", "type": "boolean", "description": "Whether the user copied this AI response content. An implicit positive quality signal." }, { "name": "[Agent] Was Cached", "type": "boolean", "description": "Whether this response was served from a semantic/full-response cache (distinct from token-level prompt caching)." }, { "name": "[Agent] Model Tier", "type": "string", "description": "Model tier classification: 'fast' (GPT-4o-mini, Haiku, Flash), 'standard' (GPT-4o, Sonnet, Pro), or 'reasoning' (o1, o3, DeepSeek-R1). Auto-inferred from model name." }, { "name": "[Agent] Has Attachments", "type": "boolean", "description": "Whether this AI response includes generated attachments (images, charts, files)." }, { "name": "[Agent] Attachment Types", "type": "string", "description": "Distinct attachment types in this AI response. Serialized JSON array.", "is_array_type": true }, { "name": "[Agent] Attachment Count", "type": "number", "description": "Number of attachments generated by the AI in this response." }, { "name": "[Agent] Total Attachment Size Bytes", "type": "number", "description": "Total size of all AI-generated attachments in bytes." }, { "name": "[Agent] Attachments", "type": "string", "description": "Serialized JSON array of AI-generated attachment metadata." }, { "name": "[Agent] Message Labels", "type": "string", "description": "Serialized JSON array of MessageLabel objects attached to this AI response." }, { "name": "[Agent] Message Label Map", "type": "string", "description": "Serialized JSON map of label key to value for quick lookup." } ] }, { "event_type": "[Agent] Tool Call", "description": "Fired when an AI agent invokes a tool or function. Captures tool name, input/output (serialized JSON, respects content_mode), latency, success status, and error details. Use to identify which tools are most frequently used, slowest, and most error-prone.", "properties": [ { "name": "[Agent] Session ID", "type": "string", "description": "Unique session identifier. All events in one conversation share the same session ID.", "is_required": true }, { "name": "[Agent] Trace ID", "type": "string", "description": "Identifies one user-message-to-AI-response cycle within a session." }, { "name": "[Agent] Turn ID", "type": "number", "description": "Monotonically increasing counter for event ordering within a session." }, { "name": "[Agent] Agent ID", "type": "string", "description": "Identifies which AI agent handled the interaction (e.g., 'support-bot', 'houston')." }, { "name": "[Agent] Parent Agent ID", "type": "string", "description": "For multi-agent orchestration: the agent that delegated to this agent." }, { "name": "[Agent] Customer Org ID", "type": "string", "description": "Organization ID for multi-tenant platforms. Enables account-level group analytics." }, { "name": "[Agent] Agent Version", "type": "string", "description": "Agent code version (e.g., 'v4.2'). Enables version-over-version quality comparison." }, { "name": "[Agent] Agent Description", "type": "string", "description": "Human-readable description of the agent's purpose (e.g., 'Handles user chat requests via OpenAI GPT-4o'). Enables observability-driven agent registry from event streams." }, { "name": "[Agent] Context", "type": "string", "description": "Serialized JSON dict of arbitrary segmentation dimensions (experiment_variant, surface, feature_flag, prompt_revision, etc.)." }, { "name": "[Agent] Env", "type": "string", "description": "Deployment environment: 'production', 'staging', or 'dev'." }, { "name": "[Agent] Tags", "type": "string", "description": "User-defined tags for filtering/segmentation. Serialized JSON array of strings." }, { "name": "[Agent] Git SHA", "type": "string", "description": "Git commit SHA of the deployed agent code. Auto-captured from environment or git CLI." }, { "name": "[Agent] Git Ref", "type": "string", "description": "Git branch or tag name (e.g., 'main', 'v1.2.3'). Auto-captured from environment or git CLI." }, { "name": "[Agent] Git Repo", "type": "string", "description": "Git repository URL. Auto-captured from environment or git CLI." }, { "name": "[Agent] Stack Trace", "type": "string", "description": "Error stack trace when Is Error is true and captureStackTrace is enabled. Opt-in only — may contain file paths." }, { "name": "[Agent] Error Source", "type": "string", "description": "Origin of the error: 'provider' (LLM API error), 'tool' (tool execution failure), 'agent' (agent logic error)." }, { "name": "[Agent] SDK Version", "type": "string", "description": "Version of the amplitude-ai SDK that produced this event.", "is_required": true }, { "name": "[Agent] Ingestion Path", "type": "string", "description": "How the events were written: 'sdk', 'http_forwarder', 'warehouse_import', or 'otlp'." }, { "name": "[Agent] Source", "type": "string", "description": "Writer that produced the events, for example 'node-sdk', 'python-sdk', 'sierra', 'warehouse-sql', or 'databricks'." }, { "name": "[Agent] Content Mode", "type": "string", "description": "Privacy posture: 'full', 'metadata_only', or 'customer_enriched'. Stamped even when message text is omitted." }, { "name": "[Agent] Runtime", "type": "string", "description": "SDK runtime: 'python' or 'node'.", "is_required": true }, { "name": "[Agent] Component Type", "type": "string", "description": "Type of component that produced this event: 'user_input', 'llm', 'tool', 'embedding'.", "is_required": true }, { "name": "[Agent] Latency Ms", "type": "number", "description": "Total wall-clock latency in milliseconds for this operation.", "is_required": true }, { "name": "[Agent] Is Error", "type": "boolean", "description": "Whether this event represents an error condition.", "is_required": true }, { "name": "[Agent] Error Message", "type": "string", "description": "Error message text when Is Error is true." }, { "name": "[Agent] Error Type", "type": "string", "description": "Exception class name when Is Error is true (e.g., 'ValidationError', 'TimeoutError'). Distinct from Error Message so downstream tooling can group failures by type without parsing the message." }, { "name": "[Agent] Locale", "type": "string", "description": "User locale (e.g., 'en-US')." }, { "name": "[Agent] Span Kind", "type": "string", "description": "Classification of the span type for OTEL bridge compatibility." }, { "name": "[Amplitude] Session Replay ID", "type": "string", "description": "Links to Amplitude Session Replay (format: device_id/session_id). Enables one-click navigation from AI session to browser replay." }, { "name": "[Agent] Invocation ID", "type": "string", "description": "Unique identifier for this tool invocation (UUID). Used to link tool calls to parent messages.", "is_required": true }, { "name": "[Agent] Tool Name", "type": "string", "description": "Name of the tool/function that was invoked (e.g., 'search_docs', 'web_search').", "is_required": true }, { "name": "[Agent] Tool Type", "type": "string", "description": "Origin/class of the tool: 'python' (native in-process tool), 'mcp' (tool served by a connected MCP server), 'flow' (sub-agent delegation), or 'unknown'. Lets you segment native vs. MCP-connected tool usage without parsing the tool name or Context." }, { "name": "[Agent] Tool Owner", "type": "string", "description": "Who owns the tool: 'amplitude' (Amplitude-built/operated — native tools, sub-agents, and Amplitude's own MCP servers) or 'customer' (a server the customer connected, e.g. their own MCP server via the gateway). Segments Amplitude-internal vs. customer-connected tool usage as a first-class property, without overloading [Agent] Tool Type." }, { "name": "[Agent] Tool Success", "type": "boolean", "description": "Whether the tool call completed successfully.", "is_required": true }, { "name": "[Agent] Tool Input", "type": "string", "description": "Serialized JSON of the tool's input arguments. Only sent when content_mode='full'." }, { "name": "[Agent] Tool Output", "type": "string", "description": "Serialized JSON of the tool's output/return value. Only sent when content_mode='full'." }, { "name": "[Agent] Parent Message ID", "type": "string", "description": "The message_id of the user message that triggered this tool call. Links the tool call into the event graph." } ] }, { "event_type": "[Agent] Embedding", "description": "Fired when a vector embedding operation is performed. Captures model, provider, latency, input tokens, vector dimensions, and cost. Used for RAG pipeline analytics.", "properties": [ { "name": "[Agent] Session ID", "type": "string", "description": "Unique session identifier. All events in one conversation share the same session ID.", "is_required": true }, { "name": "[Agent] Trace ID", "type": "string", "description": "Identifies one user-message-to-AI-response cycle within a session." }, { "name": "[Agent] Turn ID", "type": "number", "description": "Monotonically increasing counter for event ordering within a session." }, { "name": "[Agent] Agent ID", "type": "string", "description": "Identifies which AI agent handled the interaction (e.g., 'support-bot', 'houston')." }, { "name": "[Agent] Parent Agent ID", "type": "string", "description": "For multi-agent orchestration: the agent that delegated to this agent." }, { "name": "[Agent] Customer Org ID", "type": "string", "description": "Organization ID for multi-tenant platforms. Enables account-level group analytics." }, { "name": "[Agent] Agent Version", "type": "string", "description": "Agent code version (e.g., 'v4.2'). Enables version-over-version quality comparison." }, { "name": "[Agent] Agent Description", "type": "string", "description": "Human-readable description of the agent's purpose (e.g., 'Handles user chat requests via OpenAI GPT-4o'). Enables observability-driven agent registry from event streams." }, { "name": "[Agent] Context", "type": "string", "description": "Serialized JSON dict of arbitrary segmentation dimensions (experiment_variant, surface, feature_flag, prompt_revision, etc.)." }, { "name": "[Agent] Env", "type": "string", "description": "Deployment environment: 'production', 'staging', or 'dev'." }, { "name": "[Agent] Tags", "type": "string", "description": "User-defined tags for filtering/segmentation. Serialized JSON array of strings." }, { "name": "[Agent] Git SHA", "type": "string", "description": "Git commit SHA of the deployed agent code. Auto-captured from environment or git CLI." }, { "name": "[Agent] Git Ref", "type": "string", "description": "Git branch or tag name (e.g., 'main', 'v1.2.3'). Auto-captured from environment or git CLI." }, { "name": "[Agent] Git Repo", "type": "string", "description": "Git repository URL. Auto-captured from environment or git CLI." }, { "name": "[Agent] SDK Version", "type": "string", "description": "Version of the amplitude-ai SDK that produced this event.", "is_required": true }, { "name": "[Agent] Ingestion Path", "type": "string", "description": "How the events were written: 'sdk', 'http_forwarder', 'warehouse_import', or 'otlp'." }, { "name": "[Agent] Source", "type": "string", "description": "Writer that produced the events, for example 'node-sdk', 'python-sdk', 'sierra', 'warehouse-sql', or 'databricks'." }, { "name": "[Agent] Content Mode", "type": "string", "description": "Privacy posture: 'full', 'metadata_only', or 'customer_enriched'. Stamped even when message text is omitted." }, { "name": "[Agent] Runtime", "type": "string", "description": "SDK runtime: 'python' or 'node'.", "is_required": true }, { "name": "[Agent] Component Type", "type": "string", "description": "Type of component that produced this event: 'user_input', 'llm', 'tool', 'embedding'.", "is_required": true }, { "name": "[Agent] Model Name", "type": "string", "description": "LLM model identifier (e.g., 'gpt-4o', 'claude-sonnet-4-20250514').", "is_required": true }, { "name": "[Agent] Provider", "type": "string", "description": "LLM provider name (e.g., 'openai', 'anthropic', 'google', 'mistral', 'bedrock').", "is_required": true }, { "name": "[Agent] Latency Ms", "type": "number", "description": "Total wall-clock latency in milliseconds for this operation.", "is_required": true }, { "name": "[Agent] Span ID", "type": "string", "description": "Unique identifier for this embedding operation (UUID).", "is_required": true }, { "name": "[Agent] Input Tokens", "type": "number", "description": "Number of input tokens processed by the embedding model." }, { "name": "[Agent] Embedding Dimensions", "type": "number", "description": "Dimensionality of the output embedding vector." }, { "name": "[Agent] Cost USD", "type": "number", "description": "Estimated cost in USD for this embedding operation." } ] }, { "event_type": "[Agent] Span", "description": "Fired for a generic pipeline operation such as vector search, rerank, guardrails, or any custom step. Captures span name, input/output state (serialized JSON), latency, and parent span hierarchy. Enables pipeline step analysis and latency attribution.", "properties": [ { "name": "[Agent] Session ID", "type": "string", "description": "Unique session identifier. All events in one conversation share the same session ID.", "is_required": true }, { "name": "[Agent] Trace ID", "type": "string", "description": "Identifies one user-message-to-AI-response cycle within a session." }, { "name": "[Agent] Turn ID", "type": "number", "description": "Monotonically increasing counter for event ordering within a session." }, { "name": "[Agent] Agent ID", "type": "string", "description": "Identifies which AI agent handled the interaction (e.g., 'support-bot', 'houston')." }, { "name": "[Agent] Parent Agent ID", "type": "string", "description": "For multi-agent orchestration: the agent that delegated to this agent." }, { "name": "[Agent] Customer Org ID", "type": "string", "description": "Organization ID for multi-tenant platforms. Enables account-level group analytics." }, { "name": "[Agent] Agent Version", "type": "string", "description": "Agent code version (e.g., 'v4.2'). Enables version-over-version quality comparison." }, { "name": "[Agent] Agent Description", "type": "string", "description": "Human-readable description of the agent's purpose (e.g., 'Handles user chat requests via OpenAI GPT-4o'). Enables observability-driven agent registry from event streams." }, { "name": "[Agent] Context", "type": "string", "description": "Serialized JSON dict of arbitrary segmentation dimensions (experiment_variant, surface, feature_flag, prompt_revision, etc.)." }, { "name": "[Agent] Env", "type": "string", "description": "Deployment environment: 'production', 'staging', or 'dev'." }, { "name": "[Agent] Tags", "type": "string", "description": "User-defined tags for filtering/segmentation. Serialized JSON array of strings." }, { "name": "[Agent] Git SHA", "type": "string", "description": "Git commit SHA of the deployed agent code. Auto-captured from environment or git CLI." }, { "name": "[Agent] Git Ref", "type": "string", "description": "Git branch or tag name (e.g., 'main', 'v1.2.3'). Auto-captured from environment or git CLI." }, { "name": "[Agent] Git Repo", "type": "string", "description": "Git repository URL. Auto-captured from environment or git CLI." }, { "name": "[Agent] Stack Trace", "type": "string", "description": "Error stack trace when Is Error is true and captureStackTrace is enabled. Opt-in only — may contain file paths." }, { "name": "[Agent] Error Source", "type": "string", "description": "Origin of the error: 'provider' (LLM API error), 'tool' (tool execution failure), 'agent' (agent logic error)." }, { "name": "[Agent] SDK Version", "type": "string", "description": "Version of the amplitude-ai SDK that produced this event.", "is_required": true }, { "name": "[Agent] Ingestion Path", "type": "string", "description": "How the events were written: 'sdk', 'http_forwarder', 'warehouse_import', or 'otlp'." }, { "name": "[Agent] Source", "type": "string", "description": "Writer that produced the events, for example 'node-sdk', 'python-sdk', 'sierra', 'warehouse-sql', or 'databricks'." }, { "name": "[Agent] Content Mode", "type": "string", "description": "Privacy posture: 'full', 'metadata_only', or 'customer_enriched'. Stamped even when message text is omitted." }, { "name": "[Agent] Runtime", "type": "string", "description": "SDK runtime: 'python' or 'node'.", "is_required": true }, { "name": "[Agent] Latency Ms", "type": "number", "description": "Total wall-clock latency in milliseconds for this operation.", "is_required": true }, { "name": "[Agent] Is Error", "type": "boolean", "description": "Whether this event represents an error condition.", "is_required": true }, { "name": "[Agent] Error Message", "type": "string", "description": "Error message text when Is Error is true." }, { "name": "[Agent] Error Type", "type": "string", "description": "Exception class name when Is Error is true (e.g., 'ValidationError', 'TimeoutError'). Distinct from Error Message so downstream tooling can group failures by type without parsing the message." }, { "name": "[Agent] Span ID", "type": "string", "description": "Unique identifier for this span (UUID).", "is_required": true }, { "name": "[Agent] Span Name", "type": "string", "description": "Name of the operation (e.g., 'rag_pipeline', 'vector_search', 'rerank').", "is_required": true }, { "name": "[Agent] Parent Span ID", "type": "string", "description": "Span ID of the parent span for nested pipeline steps." }, { "name": "[Agent] Input State", "type": "string", "description": "Serialized JSON of the span's input state. Only sent when content_mode='full'." }, { "name": "[Agent] Output State", "type": "string", "description": "Serialized JSON of the span's output state. Only sent when content_mode='full'." } ] }, { "event_type": "[Agent] Session End", "description": "Fired when a session is explicitly closed by the SDK (via track_session_end() or Session context manager exit). Can carry optional enrichments and abandonment tracking. Triggers server-side enrichment when content_mode='full'.", "properties": [ { "name": "[Agent] Session ID", "type": "string", "description": "Unique session identifier. All events in one conversation share the same session ID.", "is_required": true }, { "name": "[Agent] Trace ID", "type": "string", "description": "Identifies one user-message-to-AI-response cycle within a session." }, { "name": "[Agent] Turn ID", "type": "number", "description": "Monotonically increasing counter for event ordering within a session." }, { "name": "[Agent] Agent ID", "type": "string", "description": "Identifies which AI agent handled the interaction (e.g., 'support-bot', 'houston')." }, { "name": "[Agent] Parent Agent ID", "type": "string", "description": "For multi-agent orchestration: the agent that delegated to this agent." }, { "name": "[Agent] Customer Org ID", "type": "string", "description": "Organization ID for multi-tenant platforms. Enables account-level group analytics." }, { "name": "[Agent] Agent Version", "type": "string", "description": "Agent code version (e.g., 'v4.2'). Enables version-over-version quality comparison." }, { "name": "[Agent] Agent Description", "type": "string", "description": "Human-readable description of the agent's purpose (e.g., 'Handles user chat requests via OpenAI GPT-4o'). Enables observability-driven agent registry from event streams." }, { "name": "[Agent] Context", "type": "string", "description": "Serialized JSON dict of arbitrary segmentation dimensions (experiment_variant, surface, feature_flag, prompt_revision, etc.)." }, { "name": "[Agent] Env", "type": "string", "description": "Deployment environment: 'production', 'staging', or 'dev'." }, { "name": "[Agent] Tags", "type": "string", "description": "User-defined tags for filtering/segmentation. Serialized JSON array of strings." }, { "name": "[Agent] Git SHA", "type": "string", "description": "Git commit SHA of the deployed agent code. Auto-captured from environment or git CLI." }, { "name": "[Agent] Git Ref", "type": "string", "description": "Git branch or tag name (e.g., 'main', 'v1.2.3'). Auto-captured from environment or git CLI." }, { "name": "[Agent] Git Repo", "type": "string", "description": "Git repository URL. Auto-captured from environment or git CLI." }, { "name": "[Agent] SDK Version", "type": "string", "description": "Version of the amplitude-ai SDK that produced this event.", "is_required": true }, { "name": "[Agent] Ingestion Path", "type": "string", "description": "How the events were written: 'sdk', 'http_forwarder', 'warehouse_import', or 'otlp'." }, { "name": "[Agent] Source", "type": "string", "description": "Writer that produced the events, for example 'node-sdk', 'python-sdk', 'sierra', 'warehouse-sql', or 'databricks'." }, { "name": "[Agent] Content Mode", "type": "string", "description": "Privacy posture: 'full', 'metadata_only', or 'customer_enriched'. Stamped even when message text is omitted." }, { "name": "[Agent] Runtime", "type": "string", "description": "SDK runtime: 'python' or 'node'.", "is_required": true }, { "name": "[Agent] Enrichments", "type": "string", "description": "Serialized JSON of SessionEnrichments (topic classifications, rubric scores, outcome, flags). Attached when enrichments are provided at session close." }, { "name": "[Agent] Abandonment Turn", "type": "number", "description": "Turn ID of the last user message that received an AI response before the user left. Low values (e.g., 1) strongly signal first-response dissatisfaction." }, { "name": "[Agent] Session Idle Timeout Minutes", "type": "number", "description": "Custom idle timeout for this session (default 30 min). Tells the server how long to wait before auto-closing." } ] }, { "event_type": "[Agent] Session Enrichment", "description": "Fired when a customer provides structured session classifications via track_session_enrichment(). Used with content_mode='customer_enriched' for teams who run their own classifiers. Distinct from the server-generated [Agent] Session Record. Contains serialized SessionEnrichments (topics, rubrics, outcome, flags) as a single JSON property.", "properties": [ { "name": "[Agent] Session ID", "type": "string", "description": "Unique session identifier. All events in one conversation share the same session ID.", "is_required": true }, { "name": "[Agent] Trace ID", "type": "string", "description": "Identifies one user-message-to-AI-response cycle within a session." }, { "name": "[Agent] Turn ID", "type": "number", "description": "Monotonically increasing counter for event ordering within a session." }, { "name": "[Agent] Agent ID", "type": "string", "description": "Identifies which AI agent handled the interaction (e.g., 'support-bot', 'houston')." }, { "name": "[Agent] Parent Agent ID", "type": "string", "description": "For multi-agent orchestration: the agent that delegated to this agent." }, { "name": "[Agent] Customer Org ID", "type": "string", "description": "Organization ID for multi-tenant platforms. Enables account-level group analytics." }, { "name": "[Agent] Agent Version", "type": "string", "description": "Agent code version (e.g., 'v4.2'). Enables version-over-version quality comparison." }, { "name": "[Agent] Agent Description", "type": "string", "description": "Human-readable description of the agent's purpose (e.g., 'Handles user chat requests via OpenAI GPT-4o'). Enables observability-driven agent registry from event streams." }, { "name": "[Agent] Context", "type": "string", "description": "Serialized JSON dict of arbitrary segmentation dimensions (experiment_variant, surface, feature_flag, prompt_revision, etc.)." }, { "name": "[Agent] Env", "type": "string", "description": "Deployment environment: 'production', 'staging', or 'dev'." }, { "name": "[Agent] Tags", "type": "string", "description": "User-defined tags for filtering/segmentation. Serialized JSON array of strings." }, { "name": "[Agent] Git SHA", "type": "string", "description": "Git commit SHA of the deployed agent code. Auto-captured from environment or git CLI." }, { "name": "[Agent] Git Ref", "type": "string", "description": "Git branch or tag name (e.g., 'main', 'v1.2.3'). Auto-captured from environment or git CLI." }, { "name": "[Agent] Git Repo", "type": "string", "description": "Git repository URL. Auto-captured from environment or git CLI." }, { "name": "[Agent] SDK Version", "type": "string", "description": "Version of the amplitude-ai SDK that produced this event.", "is_required": true }, { "name": "[Agent] Ingestion Path", "type": "string", "description": "How the events were written: 'sdk', 'http_forwarder', 'warehouse_import', or 'otlp'." }, { "name": "[Agent] Source", "type": "string", "description": "Writer that produced the events, for example 'node-sdk', 'python-sdk', 'sierra', 'warehouse-sql', or 'databricks'." }, { "name": "[Agent] Content Mode", "type": "string", "description": "Privacy posture: 'full', 'metadata_only', or 'customer_enriched'. Stamped even when message text is omitted." }, { "name": "[Agent] Runtime", "type": "string", "description": "SDK runtime: 'python' or 'node'.", "is_required": true }, { "name": "[Agent] Enrichments", "type": "string", "description": "Serialized JSON of SessionEnrichments: topic_classifications, rubrics, overall_outcome, quality_score, sentiment_score, boolean flags, agent chain metadata, and message labels.", "is_required": true } ] }, { "event_type": "[Agent] Score", "description": "Quality signal attached to a message or session, sent by the customer via the SDK's score() method. Covers user feedback (source='user', e.g., thumbs up/down), customer-run automated evals (source='ai', e.g., LLM-as-judge), and human annotations (source='reviewer'). Server-side enrichment rubric scores are emitted as [Agent] Evaluator Result (output_type='score'), not this event type.", "properties": [ { "name": "[Agent] Session ID", "type": "string", "description": "Unique session identifier. All events in one conversation share the same session ID.", "is_required": true }, { "name": "[Agent] Trace ID", "type": "string", "description": "Identifies one user-message-to-AI-response cycle within a session." }, { "name": "[Agent] Turn ID", "type": "number", "description": "Monotonically increasing counter for event ordering within a session." }, { "name": "[Agent] Agent ID", "type": "string", "description": "Identifies which AI agent handled the interaction (e.g., 'support-bot', 'houston')." }, { "name": "[Agent] Parent Agent ID", "type": "string", "description": "For multi-agent orchestration: the agent that delegated to this agent." }, { "name": "[Agent] Customer Org ID", "type": "string", "description": "Organization ID for multi-tenant platforms. Enables account-level group analytics." }, { "name": "[Agent] Agent Version", "type": "string", "description": "Agent code version (e.g., 'v4.2'). Enables version-over-version quality comparison." }, { "name": "[Agent] Agent Description", "type": "string", "description": "Human-readable description of the agent's purpose (e.g., 'Handles user chat requests via OpenAI GPT-4o'). Enables observability-driven agent registry from event streams." }, { "name": "[Agent] Context", "type": "string", "description": "Serialized JSON dict of arbitrary segmentation dimensions (experiment_variant, surface, feature_flag, prompt_revision, etc.)." }, { "name": "[Agent] Env", "type": "string", "description": "Deployment environment: 'production', 'staging', or 'dev'." }, { "name": "[Agent] Tags", "type": "string", "description": "User-defined tags for filtering/segmentation. Serialized JSON array of strings." }, { "name": "[Agent] Git SHA", "type": "string", "description": "Git commit SHA of the deployed agent code. Auto-captured from environment or git CLI." }, { "name": "[Agent] Git Ref", "type": "string", "description": "Git branch or tag name (e.g., 'main', 'v1.2.3'). Auto-captured from environment or git CLI." }, { "name": "[Agent] Git Repo", "type": "string", "description": "Git repository URL. Auto-captured from environment or git CLI." }, { "name": "[Agent] SDK Version", "type": "string", "description": "Version of the amplitude-ai SDK that produced this event.", "is_required": true }, { "name": "[Agent] Ingestion Path", "type": "string", "description": "How the events were written: 'sdk', 'http_forwarder', 'warehouse_import', or 'otlp'." }, { "name": "[Agent] Source", "type": "string", "description": "Writer that produced the events, for example 'node-sdk', 'python-sdk', 'sierra', 'warehouse-sql', or 'databricks'." }, { "name": "[Agent] Content Mode", "type": "string", "description": "Privacy posture: 'full', 'metadata_only', or 'customer_enriched'. Stamped even when message text is omitted." }, { "name": "[Agent] Runtime", "type": "string", "description": "SDK runtime: 'python' or 'node'.", "is_required": true }, { "name": "[Agent] Score Name", "type": "string", "description": "Name of the score (e.g., 'user-feedback', 'task_completion', 'accuracy', 'groundedness').", "is_required": true }, { "name": "[Agent] Score Value", "type": "number", "description": "Numeric score value. Binary (0/1), continuous (0.0-1.0), or rating scale (1-5).", "is_required": true }, { "name": "[Agent] Target ID", "type": "string", "description": "The message_id or session_id being scored.", "is_required": true }, { "name": "[Agent] Target Type", "type": "string", "description": "What is being scored: 'message' or 'session'.", "is_required": true }, { "name": "[Agent] Evaluation Source", "type": "string", "description": "Source of the evaluation: 'user' (end-user feedback), 'ai' (automated/server pipeline), or 'reviewer' (human expert).", "is_required": true }, { "name": "[Agent] Provider Request ID", "type": "string", "description": "Provider-owned inference identifier. On AI Response this is captured from the provider response; on Score it is present only when explicitly supplied." }, { "name": "[Agent] Comment", "type": "string", "description": "Optional text explanation for the score (respects content_mode)." }, { "name": "[Agent] Taxonomy Version", "type": "string", "description": "Which taxonomy config version produced this enrichment (from ai_category_config.config_version_id)." }, { "name": "[Agent] Evaluated At", "type": "number", "description": "Epoch milliseconds when this enrichment/evaluation was computed." }, { "name": "[Agent] Evaluator Model", "type": "string", "description": "LLM model identifier used to produce this evaluator output." }, { "name": "[Agent] Score Label", "type": "string", "description": "Direction-neutral magnitude label derived from score value. Default 5-tier: very_high (>=0.8), high (>=0.6), moderate (>=0.4), low (>=0.2), very_low (>=0.0). Server-side only." } ] }, { "event_type": "[Agent] Session Record", "description": "Fired once per enriched session by the server-side enrichment pipeline. Contains session-level facts: overall outcome, turn count, boolean flags (has_task_failure, has_negative_feedback, has_technical_failure, has_data_quality_issues), cost, and user friction patterns. Enables cohorts like 'users with 3+ task failures in 30 days'.", "properties": [ { "name": "[Agent] Session ID", "type": "string", "description": "Unique session identifier. All events in one conversation share the same session ID.", "is_required": true }, { "name": "[Agent] Agent ID", "type": "string", "description": "Identifies which AI agent handled the interaction (e.g., 'support-bot', 'houston').", "is_required": true }, { "name": "[Agent] Org ID", "type": "string", "description": "The Amplitude organization ID owning the project where this event is tracked.", "is_required": true }, { "name": "[Agent] Customer Org ID", "type": "string", "description": "Organization ID for multi-tenant platforms. Enables account-level group analytics." }, { "name": "[Agent] Evaluation Source", "type": "string", "description": "Source of the evaluation: 'user' (end-user feedback), 'ai' (automated/server pipeline), or 'reviewer' (human expert).", "is_required": true }, { "name": "[Agent] Taxonomy Version", "type": "string", "description": "Which taxonomy config version produced this enrichment (from ai_category_config.config_version_id).", "is_required": true }, { "name": "[Agent] Evaluated At", "type": "number", "description": "Epoch milliseconds when this enrichment/evaluation was computed.", "is_required": true }, { "name": "[Agent] Turn Count", "type": "number", "description": "Number of conversation turns in this session.", "is_required": true }, { "name": "[Agent] Session Total Tokens", "type": "number", "description": "Total LLM tokens consumed across all turns in this session." }, { "name": "[Agent] Session Avg Latency Ms", "type": "number", "description": "Average AI response latency in milliseconds across the session." }, { "name": "[Agent] Request Complexity", "type": "string", "description": "Complexity classification of the user's request: 'simple', 'moderate', 'complex', or 'ambiguous'." }, { "name": "[Agent] Has Task Failure", "type": "boolean", "description": "Whether the agent failed to complete the user's request.", "is_required": true }, { "name": "[Agent] Has Negative Feedback", "type": "boolean", "description": "Whether the user expressed dissatisfaction during the session.", "is_required": true }, { "name": "[Agent] Has Technical Failure", "type": "boolean", "description": "Whether technical errors occurred (tool timeouts, API failures, etc.).", "is_required": true }, { "name": "[Agent] Has Data Quality Issues", "type": "boolean", "description": "Whether the AI output had data quality problems (wrong data, hallucinations, etc.).", "is_required": true }, { "name": "[Agent] Models Used", "type": "string", "description": "LLM models used in this session. JSON array of strings.", "is_array_type": true }, { "name": "[Agent] Root Agent Name", "type": "string", "description": "Entry-point agent in multi-agent flows." }, { "name": "[Agent] Agent Chain Depth", "type": "number", "description": "Number of agents in the delegation chain." }, { "name": "[Agent] Task Failure Type", "type": "string", "description": "Specific failure type when has_task_failure is true (e.g., 'wrong_answer', 'unable_to_complete')." }, { "name": "[Agent] Technical Error Count", "type": "number", "description": "Count of technical errors that occurred during the session." }, { "name": "[Agent] Error Categories", "type": "string", "description": "Categorized error types (e.g., 'chart_not_found', 'timeout'). JSON array of strings.", "is_array_type": true }, { "name": "[Agent] User Friction", "type": "string", "description": "Detected user friction patterns (e.g., 'retry_storm', 'clarification_loop', 'early_abandonment'). JSON array of strings.", "is_array_type": true }, { "name": "[Agent] Session Cost USD", "type": "number", "description": "Total LLM cost in USD for this AI session (aggregated from per-message costs)." }, { "name": "[Agent] Quality Score", "type": "number", "description": "Overall quality score (0.0-1.0) computed by the enrichment pipeline for this session." }, { "name": "[Agent] Sentiment Score", "type": "number", "description": "User sentiment score (0.0-1.0) inferred from the conversation by the enrichment pipeline." }, { "name": "[Agent] Task Failure Reason", "type": "string", "description": "Explanation of why the task failed when has_task_failure is true (e.g., 'chart data source unavailable')." }, { "name": "[Agent] Agent Chain", "type": "string", "description": "Serialized JSON array of agent IDs representing the delegation chain in multi-agent flows.", "is_array_type": true }, { "name": "[Agent] Project ID", "type": "string", "description": "Amplitude project ID that owns the AI session being evaluated." }, { "name": "[Agent] Has User Feedback", "type": "boolean", "description": "Whether the session received explicit user feedback (thumbs up/down, rating).", "is_required": true }, { "name": "[Agent] User Score", "type": "number", "description": "Aggregate user feedback score for the session (0.0-1.0). Present only when has_user_feedback is true." }, { "name": "[Agent] Agent Version", "type": "string", "description": "Agent code version (e.g., 'v4.2'). Enables version-over-version quality comparison." }, { "name": "[Agent] Agent Description", "type": "string", "description": "Human-readable description of the agent's purpose (e.g., 'Handles user chat requests via OpenAI GPT-4o'). Enables observability-driven agent registry from event streams." }, { "name": "[Agent] Context", "type": "string", "description": "Serialized JSON dict of arbitrary segmentation dimensions (experiment_variant, surface, feature_flag, prompt_revision, etc.)." }, { "name": "[Agent] Task Completed", "type": "string", "description": "OOTB detector result: 'True' if agent completed user's request, 'False' otherwise." }, { "name": "[Agent] Task Completed Rationale", "type": "string", "description": "Brief rationale for the task completion determination." }, { "name": "[Agent] Task Completed Evidence", "type": "string", "description": "Supporting evidence for the task completion determination." }, { "name": "[Agent] Response Quality", "type": "string", "description": "OOTB detector result: 'True' if response was accurate/clear/helpful, 'False' otherwise." }, { "name": "[Agent] Response Quality Rationale", "type": "string", "description": "Brief rationale for the response quality determination." }, { "name": "[Agent] Response Quality Evidence", "type": "string", "description": "Supporting evidence for the response quality determination." }, { "name": "[Agent] Session Outcome", "type": "string", "description": "OOTB classifier result for how the session ended (e.g., 'Response Provided', 'Unable to Complete', 'Escalated')." }, { "name": "[Agent] Session Outcome Rationale", "type": "string", "description": "Brief rationale for the session outcome classification." }, { "name": "[Agent] Session Safety", "type": "string", "description": "OOTB classifier result for session safety (e.g., 'normal', 'off_topic', 'prompt_injection', 'abuse')." }, { "name": "[Agent] Session Safety Rationale", "type": "string", "description": "Brief rationale for the session safety classification." }, { "name": "[Agent] User Intent", "type": "string", "description": "OOTB classifier result for user's primary intent (e.g., 'Information Request', 'Task Execution', 'Content Creation')." }, { "name": "[Agent] User Intent Rationale", "type": "string", "description": "Brief rationale for the user intent classification." }, { "name": "[Agent] Has User Friction", "type": "boolean", "description": "OOTB detector result: whether conversation exhibited user friction patterns (retry storms, clarification loops, etc.)." }, { "name": "[Agent] User Friction Rationale", "type": "string", "description": "Brief rationale for user friction detection." }, { "name": "[Agent] Detected User Friction", "type": "string", "description": "Specific user friction patterns detected (e.g., 'retry_storm', 'tool_cascade_fail'). JSON array.", "is_array_type": true }, { "name": "[Agent] Detected Data Quality Issues", "type": "string", "description": "Specific data quality issues detected. JSON array.", "is_array_type": true } ] }, { "event_type": "[Agent] Topic Classification", "deprecated": true, "description": "DEPRECATED: Replaced by [Agent] Evaluator Result. Previously fired once per topic model per session by the server-side enrichment pipeline. A session with 3 topic models (e.g., query_intent, product_area, error_domain) produced 3 of these events. Property names are always the same; the topic model name goes in the value.", "properties": [ { "name": "[Agent] Session ID", "type": "string", "description": "Unique session identifier. All events in one conversation share the same session ID.", "is_required": true }, { "name": "[Agent] Agent ID", "type": "string", "description": "Identifies which AI agent handled the interaction (e.g., 'support-bot', 'houston').", "is_required": true }, { "name": "[Agent] Org ID", "type": "string", "description": "The Amplitude organization ID owning the project where this event is tracked.", "is_required": true }, { "name": "[Agent] Evaluation Source", "type": "string", "description": "Source of the evaluation: 'user' (end-user feedback), 'ai' (automated/server pipeline), or 'reviewer' (human expert).", "is_required": true }, { "name": "[Agent] Taxonomy Version", "type": "string", "description": "Which taxonomy config version produced this enrichment (from ai_category_config.config_version_id).", "is_required": true }, { "name": "[Agent] Evaluated At", "type": "number", "description": "Epoch milliseconds when this enrichment/evaluation was computed.", "is_required": true }, { "name": "[Agent] Topic", "type": "string", "description": "Which topic model this classification is for (e.g., 'product_area', 'query_intent', 'error_domain').", "is_required": true }, { "name": "[Agent] Selection Mode", "type": "string", "description": "Whether this topic model uses 'single' (MECE) or 'multiple' (multi-label) selection.", "is_required": true }, { "name": "[Agent] Primary Label", "type": "string", "description": "Primary classification value (e.g., 'charts', 'billing_issues')." }, { "name": "[Agent] Secondary Label", "type": "string", "description": "Secondary classifications for multi-label topics. JSON array of strings.", "is_array_type": true }, { "name": "[Agent] Subcategories", "type": "string", "description": "Subcategories for finer classification within the primary topic (e.g., 'TREND_ANALYSIS', 'WRONG_EVENT'). JSON array of strings.", "is_array_type": true }, { "name": "[Agent] Evaluator Model", "type": "string", "description": "LLM model identifier used to produce this evaluator output." } ] }, { "event_type": "[Agent] Evaluator Result", "description": "Fired once per custom evaluator per session. Covers classifiers, detectors, and scorers — distinguished by [Agent] Evaluator Output Type. OOTB evaluators are excluded (their results are de-normalized on Session Record).", "properties": [ { "name": "[Agent] Session ID", "type": "string", "description": "Unique session identifier. All events in one conversation share the same session ID.", "is_required": true }, { "name": "[Agent] Agent ID", "type": "string", "description": "Identifies which AI agent handled the interaction (e.g., 'support-bot', 'houston').", "is_required": true }, { "name": "[Agent] Org ID", "type": "string", "description": "The Amplitude organization ID owning the project where this event is tracked.", "is_required": true }, { "name": "[Agent] Evaluation Source", "type": "string", "description": "Source of the evaluation: 'user' (end-user feedback), 'ai' (automated/server pipeline), or 'reviewer' (human expert).", "is_required": true }, { "name": "[Agent] Evaluator Version", "type": "string", "description": "Config version ID that produced this result.", "is_required": true }, { "name": "[Agent] Evaluated At", "type": "number", "description": "Epoch milliseconds when this enrichment/evaluation was computed.", "is_required": true }, { "name": "[Agent] Evaluator Name", "type": "string", "description": "Human-readable evaluator name (primary group-by for users).", "is_required": true }, { "name": "[Agent] Evaluator Output Type", "type": "string", "description": "Discriminator for the evaluator kind: 'classification', 'score', or 'binary'.", "is_required": true }, { "name": "[Agent] Selection Mode", "type": "string", "description": "Whether this evaluator uses 'single' or 'multiple' selection. Classification only." }, { "name": "[Agent] Primary Label", "type": "string", "description": "Primary classification label. Classification only." }, { "name": "[Agent] Secondary Label", "type": "string", "description": "Secondary labels for multi-label evaluators. Classification only.", "is_array_type": true }, { "name": "[Agent] Subcategories", "type": "string", "description": "Finer classification within the primary label. Classification only.", "is_array_type": true }, { "name": "[Agent] Binary Label", "type": "boolean", "description": "Whether the condition was detected. Binary only." }, { "name": "[Agent] Score Value", "type": "number", "description": "Numeric score assigned by the evaluator. Score only." }, { "name": "[Agent] Score Label", "type": "string", "description": "Human-readable tier (e.g., 'good', 'poor'). Score only." }, { "name": "[Agent] Target ID", "type": "string", "description": "ID of the scored entity (session_id). Score only." }, { "name": "[Agent] Target Type", "type": "string", "description": "Type of scored entity (e.g., 'session'). Score only." }, { "name": "[Agent] Improvement Opportunities", "type": "string", "description": "Suggestions for how the agent could improve. Score only." }, { "name": "[Agent] Rationale", "type": "string", "description": "LLM-generated explanation for the result." }, { "name": "[Agent] Evidence", "type": "string", "description": "Supporting evidence (quotes, observations) for the result." }, { "name": "[Agent] Evaluator Model", "type": "string", "description": "LLM model identifier used to produce this evaluator output." }, { "name": "[Agent] Evaluator Enrichment Cost USD", "type": "number", "description": "Cost in USD of running this specific evaluator's LLM inference. Customer-attributable enrichment cost for this evaluator; distinct from the session's own LLM cost ([Agent] Session Cost USD)." } ] } ] }