Respond to a Query Agent

The Respond to a Query agent is the core, general-purpose response agent on the Ema platform. It generates text responses by synthesizing any combination of typed inputs -- search results, documents, conversation history, structured entities, and free-form text -- using LLM reasoning. Unlike specialized response agents that are tuned for a single input type, Respond to a Query uses the full Type System through Named Inputs, making it the right choice whenever no specialized agent fits your specific input combination.

Use Cases

• You need a flexible response agent that can work with any combination of upstream data.
• You want to generate a response that synthesizes information from multiple sources (e.g., search results plus extracted entities plus conversation history).
• No specialized response agent fits your specific input combination.
• You want to route custom typed data (documents, extracted entities, chat conversations) through a single response step without a custom agent.

Inputs

Respond to a Query uses Named Inputs for its "Additional Context" section, allowing any number of labeled, typed fields to be bound from upstream agents. Common named inputs include:

You can add your own named input fields for any supported type -- see Named Inputs and Outputs for the full list of supported primitive and framework types and instructions for adding custom fields.

Outputs

Configurations

Type-Aware Input Handling

Because Respond to a Query uses the platform Type System, each input type is prepared for LLM consumption according to its type contract:

• SearchResults are flattened with snippet text, source metadata, and relevance scores so the model can cite specific passages.
• Documents are passed with their extracted text content; the model can reference sections by name.
• Conversation history is formatted as turn-by-turn dialogue, allowing the model to track references like "the order I mentioned earlier."
• Entities (JSON) are rendered as structured key-value pairs the model can embed in the response.
• Text with Sources is presented with inline citation markers.

This means you do not need intermediate formatting agents between typed upstream data and Respond to a Query.

Choosing the Right Response Agent

• Use Respond to a Query when you need to synthesize multiple input types, or when your input combination is non-standard.
• Use Respond using Search Results when your input is purely search results and you need inline citations out of the box.
• Use Respond using Action Calling Results when your input is tool execution results from Intelligent Actions.
• Use Fixed Response when the response is deterministic and template-based.

How to Use This Agent

Synthesize search results and extracted entities into a single grounded response:

trigger -> knowledge_search --------\
 -> extract_entities --------> respond_to_a_query -> workflow_output

Combine conversation history with a document reference:

chat_trigger -> conversation_summarizer ---\
 -> document_synthesis ---> respond_to_a_query -> workflow_output

Related Agents

• Respond using Search Results -- optimized for search-grounded responses with citations.
• Respond using Action Calling Results -- for formatting tool execution results.
• Custom Agent -- for arbitrary LLM tasks beyond response generation.
• Fixed Response -- for deterministic, template-based responses.