Cortex Agents Run API¶

There are two methods to interact with an Agent:

Build an agent object and reference this agent object in a request to the agent:run API.
Call agent:run directly without an agent object. You provide the configuration in the request body of agent:run.

Both methods use streaming APIs that respond with the server-sent events specified under Streaming Responses.

Agent run request with agent object¶

POST /api/v2/databases/{database}/schemas/{schema}/agents/{name}:run

Sends a user query to the agent object and returns its response as a stream of events.

Path parameters¶

Parameter	Description
`database`	(Required) The database containing the agent. You can use the `/api/v2/databases` GET request to get a list of available databases.
`schema`	(Required) The schema containing the agent. You can use the `/api/v2/databases/{database}/schemas` GET request to get a list of available schemas for the specified database.
`name`	(Required) The name of the agent.

Request headers¶

Header	Description
`Authorization`	(Required) Authorization token. See Authentication.
`Content-Type`	(Required) application/json

Request body¶

Field	Type	Description
`thread_id`	integer	The thread ID for the conversation. If thread_id is used, then parent_message_id must be passed as well.
`parent_message_id`	integer	The ID of the parent thread in case you are forking the interaction. The initial parent_message_id should be 0.
`messages`	array of Message	If thread_id and parent_message_id are passed in the request, messages includes the current user message in the conversation. Else, messages includes the conversation history and the current message. Messages contains both user queries and assistant responses in chronological order.
`tool_choice`	ToolChoice	Configures how the agent should select and use tools during the interaction. Controls whether tool use is automatic, required, or whether specific tools should be used.

Example

{
  "thread_id": 0,
  "parent_message_id": 0,
  "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "What is the total revenue for 2023?"
        }
      ]
    }
  ],
  "tool_choice": {
    "type": "auto",
    "name": [
      "analyst_tool",
      "search_tool"
    ]
  }
}

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Agent run without an agent object¶

POST /api/v2/cortex/agent:run

Sends a user query to the Cortex Agents service provided in the request body and returns its response. Interacts with the agent without creating an agent object.

Note

Before September 1st, 2025, the request and response schemas for the agent:run API were different from the schema listed in this document. Previously, the orchestration was static and the same sequence of tools was used to generate an answer. agent:run now has an updated schema for both the request and response. In addition, the API now dynamically orchestrates and iterates to arrive at the final response. We recommend using the schema described in this document for an improved end-user experience.

To use the legacy schema and behavior, use the following schema:

{
  "model": "claude-4-sonnet",
  "messages": [
     {"role":"user", "content": [] }
  ]
}

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Request headers¶

Header	Description
`Authorization`	(Required) Authorization token. See Authentication.
`Content-Type`	(Required) application/json

Request body¶

Field	Type	Description
`thread_id`	integer	The thread ID for the conversation. If thread_id is used, then parent_message_id must be passed as well.
`parent_message_id`	integer	The ID of the parent thread in case you are forking the interaction. The initial parent_message_id should be 0.
`messages`	array of Message	If thread_id and parent_message_id are passed in the request, messages includes the current user message in the conversation. Else, messages includes the conversation history and the current message. Messages contains both user queries and assistant responses in chronological order.
`tool_choice`	ToolChoice	Configures how the agent should select and use tools during the interaction. Controls whether tool use is automatic, required, or whether specific tools should be used.
`models`	ModelConfig	LLM configuration for each step of the request. Currently only available for the `orchestration` step.
`instructions`	AgentInstructions	Custom instructions for the Agent.
`tools`	array of Tool	List of tools available for the agent to use. Tools may have a corresponding configuration in tool_resources.
`tool_resources`	map of ToolResource	Configuration for each tool referenced in the tools array. Keys must match the name of the respective tool.

Example

{
  "thread_id": 0,
  "parent_message_id": 0,
  "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "What is the total revenue for 2023?"
        }
      ]
    }
  ],
  "tool_choice": {
    "type": "auto",
    "name": [
      "analyst_tool",
      "search_tool"
    ]
  },
  "models": {
    "orchestration": "claude-4-sonnet"
  },
  "instructions": {
    "response": "You will respond in a friendly but concise manner",
    "orchestration": "For any query related to revenue we should use Analyst; For all policy questions we should use Search",
    "system": "You are a friendly agent ..."
  },
  "tools": [
    {
      "tool_spec": {
        "type": "generic",
        "name": "get_weather",
        "description": "Fetch the delivery revenue for a location.",
        "input_schema": {
          "type": "object",
          "properties": {
            "location": {
              "type": "string",
              "description": "The city and state, e.g. San Francisco, CA"
            }
          }
        },
        "required": [
          "location"
        ]
      }
    }
  ],
  "tool_resources": {
    "get_revenue": {
      "type": "function",
      "execution_environment": {
        "type": "warehouse",
        "warehouse": "MY_WH"
      },
      "identifier": "DB.SCHEMA.UDF"
    }
  }
}

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Streaming responses¶

The agent:run API provides streaming responses. The server streams back events. This allows you to display responses in your application, token-by-token, as they are generated by the Agent. Each event streamed in the API response has a strictly typed schema. You can find a list of all of the events in the following section and select to which ones you’d like to subscribe.

The last event sent by the API is a response event. This event contains the entire agent output. You can use this as the agent’s final response. For any non-streaming clients, you can subscribe to this event because it is the logical aggregation of all prior events. If you don’t want to use streaming responses, wait for the response event and ignore all prior events.

The majority of the other events streamed can be split into two categories: Delta and Content Items.

Delta events represent a single token generated by the Agent. By listening to these events, you can create a typewriter effect. The main delta events are response.thinking.delta, which represents a reasoning token, and response.text.delta, which represent an answer token.

Content Item events represent elements from the content array in the final agent response.

Note

Make sure your application can handle unknown event types.

Example Response

event: response.status
data: {"message":"Planning the next steps","status":"planning"}

event: response.thinking.delta
data: {"content_index":0,"text":"\nThe user is asking for a"}

event: response.thinking.delta
data: {"content_index":0,"text":" chart showing the"}

...
...
...

event: response.status
data: {"message":"Reviewing the results","status":"reasoning_agent_stop"}

event: response.status
data: {"message":"Forming the answer","status":"proceeding_to_answer"}

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`response`¶

Event streamed when the final response is available. This is the last event emitted, it represents the aggregation of all other events previously streamed.

Field	Type	Description
`role`	string	The role for the message. Always `assistant` in the API response.
`content`	array of MessageContentItem	The content generated by the agent.

Example

{
  "role": "assistant",
  "content": [
    {
      "type": "chart",
      "chart": {
        "tool_use_id": "toolu_123",
        "chart_spec": "{\"$schema\":\"https://vega.github.io/schema/vega-lite/v5.json\",\"data\":{...},\"mark\":\"bar\"}"
      }
    }
  ]
}

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`response.text`¶

An event streamed when a text content block is done streaming, including all the aggregated deltas for a particular content index.

Field	Type	Description
`content_index`	integer	The index in the response content array this event represents
`text`	string	A text result from the agent
`annotations`	array of Annotation	Any annotations attached to the text result (e.g. citations)
`is_elicitation`	boolean	Whether this text content is the agent asking for more information from the end user.

Example

{
  "content_index": 0,
  "text": "Lorem ipsum dolor...",
  "annotations": [
    {
      "type": "cortex_search_citation",
      "index": 0,
      "search_result_id": "cs_61987ff6-6d56-4695-83c0-1e7cfed818c7",
      "doc_id": "4ac085cb-82d0-4eb4-94f3-2672aa0599a2",
      "doc_title": "Earnings Report",
      "text": "The revenue for 2025 was..."
    }
  ],
  "is_elicitation": false
}

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`response.text.delta`¶

Event streamed when a new output text delta is generated.

Field	Type	Description
`content_index`	integer	The index in the response content array this event represents
`text`	string	The text delta
`is_elicitation`	boolean	Whether this text content is the agent asking for more information from the end user.

Example

{
  "content_index": 0,
  "text": "Hello",
  "is_elicitation": false
}

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`response.text.annotation`¶

Event streamed when an annotation is added to a text content.

Field	Type	Description
`content_index`	integer	The index in the response content array this event represents
`annotation_index`	integer	The index in the annotation array this `annotation` belongs to.
`annotation`	Annotation	The annotation object being added.

Example

{
  "content_index": 0,
  "annotation_index": 0,
  "annotation": {
    "type": "cortex_search_citation",
    "index": 0,
    "search_result_id": "cs_61987ff6-6d56-4695-83c0-1e7cfed818c7",
    "doc_id": "4ac085cb-82d0-4eb4-94f3-2672aa0599a2",
    "doc_title": "Earnings Report",
    "text": "The revenue for 2025 was..."
  }
}

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`response.thinking`¶

An event streamed when a thinking content block is done streaming, including all the aggregated deltas for a particular content index.

Field	Type	Description
`content_index`	integer	The index in the response content array this event represents
`text`	string	Thinking tokens from the agent

Example

{
  "content_index": 0,
  "text": "To answer your question I must..."
}

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`response.thinking.delta`¶

Event streamed when a thinking delta is generated.

Field	Type	Description
`content_index`	integer	The index in the response content array this event represents
`text`	string	The thinking token

Example

{
  "content_index": 0,
  "text": "lorem ipsum"
}

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`response.tool_use`¶

An event streamed when the agent requests a tool use.

Field	Type	Description
`content_index`	integer	The index in the response content array this event represents
`tool_use_id`	string	Unique identifier for this tool use. Can be used to associated tool results.
`type`	string	The type of the tool (e.g. cortex_search, cortex_analyst_text2sql)
`name`	string	The unique identifier for this tool instance
`input`	object	The structured input for this tool. The schema of this object should will vary depending on the tool spec.
`client_side_execute`	boolean	Whether the tool use is executed on the client side.

Example

{
  "content_index": 0,
  "tool_use_id": "toolu_123",
  "type": "cortex_analyst_text2sql",
  "name": "my_cortex_analyst_semantic_view",
  "input": {
    "location": "San Francisco, CA"
  },
  "client_side_execute": "true"
}

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`response.tool_result`¶

Event streamed when a tool finishes executing, including the tool result.

Field	Type	Description
`content_index`	integer	The index in the response content array this event represents
`tool_use_id`	string	Unique identifier for this tool use. Can be used to associated tool results.
`type`	string	The type of the tool (e.g. cortex_search, cortex_analyst_text2sql)
`name`	string	The unique identifier for this tool instance
`content`	array of ToolResultContent	The content on the tool result
`status`	string	The status of tool execution

Example

{
  "content_index": 0,
  "tool_use_id": "toolu_123",
  "type": "cortex_analyst_text2sql",
  "name": "my_cortex_analyst_semantic_view",
  "content": [
    {
      "type": "json",
      "json": {
        "answer": 42
      }
    }
  ],
  "status": "success"
}

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`response.tool_result.status`¶

Status update for a specific tool use.

Field	Type	Description
`tool_use_id`	string	Unique identifier for this tool use.
`tool_type`	string	The type of the tool (e.g. cortex_search, cortex_analyst_text2sql)
`status`	string	Enum for the current state.
`message`	string	A more descriptive message expanding on the current status.

Example

{
  "tool_use_id": "toolu_123",
  "tool_type": "cortex_analyst_text2sql",
  "status": "Executing SQL",
  "message": "Executing query 'SELECT * FROM my_table'"
}

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`response.tool_result.analyst.delta`¶

An delta event streamed for the Cortex Analyst tool execution

Field	Type	Description
`content_index`	integer	The index in the response content array this event represents
`tool_use_id`	string	Unique identifier for this tool use. Can be used to associated tool results.
`tool_type`	string	The type of the tool (always cortex_analyst_text2sql for this event)
`tool_name`	string	The unique identifier for this tool instance
`delta`	CortexAnalystToolResultDelta	The content delta

Example

{
  "content_index": 0,
  "tool_use_id": "toolu_123",
  "tool_type": "cortex_analyst_text2sql",
  "tool_name": "my_cortex_analyst_semantic_view",
  "delta": {
    "text": "The...",
    "think": "Thinking...",
    "sql": "SELECT...",
    "sql_explanation": "This...",
    "query_id": "707787a0-a684-4ead-adb0-3c3b62b043d9",
    "verified_query_used": false,
    "result_set": {
      "statementHandle": "707787a0-a684-4ead-adb0-3c3b62b043d9",
      "resultSetMetaData": {
        "partition": 0,
        "numRows": 0,
        "format": "jsonv2",
        "rowType": [
          {
            "name": "my_column",
            "type": "VARCHAR",
            "length": 0,
            "precision": 0,
            "scale": 0,
            "nullable": false
          }
        ]
      },
      "data": [
        [
          "row1 col1",
          "row1 col2"
        ],
        [
          "row2 col1",
          "row2 col2"
        ]
      ]
    },
    "suggestions": {
      "index": 0,
      "delta": "What..."
    }
  }
}

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`response.tool_result.sql_explanation.delta`¶

A delta event streamed for the SQL explanation tool execution

Field	Type	Description
`content_index`	integer	The index in the response content array this event represents
`tool_use_id`	string	Unique identifier for this tool use. Can be used to associated tool results.
`tool_type`	string	The type of the tool (always sql_explanation for this event)
`tool_name`	string	The unique identifier for this tool instance
`delta`	SqlExplanationToolResultDelta

Example

{
  "content_index": 0,
  "tool_use_id": "toolu_123",
  "tool_type": "sql_explanation",
  "tool_name": "my_sql_explanation_tool",
  "delta": {
    "text": "This query selects all columns"
  }
}

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`response.table`¶

An event streamed when a table content block is added.

Field	Type	Description
`content_index`	integer	The index in the response content array this event represents
`tool_use_id`	string	The ID of the tool use that generated this table
`query_id`	string	The query id of the sql query that generated this data
`result_set`	ResultSet	The SQL results to render a table. Matches the schema from Snowflake’s SQL API ResultSet (https://docs.snowflake.cn/en/developer-guide/sql-api/reference#resultset)
`title`	string	The title for this table

Example

{
  "content_index": 0,
  "tool_use_id": "toolu_123",
  "query_id": "6ac75378-6337-48a6-80ab-6de48dd680eb",
  "result_set": {
    "statementHandle": "707787a0-a684-4ead-adb0-3c3b62b043d9",
    "resultSetMetaData": {
      "partition": 0,
      "numRows": 0,
      "format": "jsonv2",
      "rowType": [
        {
          "name": "my_column",
          "type": "VARCHAR",
          "length": 0,
          "precision": 0,
          "scale": 0,
          "nullable": false
        }
      ]
    },
    "data": [
      [
        "row1 col1",
        "row1 col2"
      ],
      [
        "row2 col1",
        "row2 col2"
      ]
    ]
  },
  "title": "Revenue by Month"
}

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`response.chart`¶

An event streamed when a chart content block is added.

Field	Type	Description
`content_index`	integer	The index in the response content array this event represents
`tool_use_id`	string	The ID of the tool use that generated this chart
`chart_spec`	string	The vega-lite chart specification serialized as a string

Example

{
  "content_index": 0,
  "tool_use_id": "toolu_123",
  "chart_spec": "{\"$schema\":\"https://vega.github.io/schema/vega-lite/v5.json\",\"data\":{...},\"mark\":\"bar\"}"
}

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`response.status`¶

Status update for the agent execution.

Field	Type	Description
`status`	string	Enum for the current state.
`message`	string	A more descriptive message expanding on the current status.

Example

{
  "status": "executing_tool",
  "message": "Executing tool `my_analyst_tool`"
}

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`error`¶

Sent when a fatal errors is encountered.

Field	Type	Description
`code`	string	The Snowflake error code
`message`	string	The error message
`request_id`	string	The unique identifier for this request

Example

{
  "code": "399504",
  "message": "Error during execution",
  "request_id": "61987ff6-6d56-4695-83c0-1e7cfed818c7"
}

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Schemas¶

`AgentInstructions`¶

Field	Type	Description
`response`	string	These custom instructions are displayed when the Agent generates the final response based on the tools executed.
`orchestration`	string	These custom instructions are displayed when the Agent is planning which tools to use
`system`	string	Instructions always shown to the Agent

Example

{
  "response": "You will respond in a friendly but concise manner",
  "orchestration": "For any query related to revenue we should use Analyst; For all policy questions we should use Search",
  "system": "You are a friendly agent ..."
}

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`Annotation`¶

Field

Type

Description

type

string

The citation type (always cortex_search_citation)

index

integer

The index of the citation in the search results.

search_result_id

string

The unique identifier for the search result.

doc_id

string

The unique identifier for the document.

doc_title

string

The title of the document.

text

string

The text excerpt from the document used as the citation.

Example
{
  "type": "cortex_search_citation",
  "index": 0,
  "search_result_id": "cs_61987ff6-6d56-4695-83c0-1e7cfed818c7",
  "doc_id": "4ac085cb-82d0-4eb4-94f3-2672aa0599a2",
  "doc_title": "Earnings Report",
  "text": "The revenue for 2025 was..."
}
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Field	Type	Description
`type`	string	The citation type (always `cortex_search_citation`)
`index`	integer	The index of the citation in the search results.
`search_result_id`	string	The unique identifier for the search result.
`doc_id`	string	The unique identifier for the document.
`doc_title`	string	The title of the document.
`text`	string	The text excerpt from the document used as the citation.

`ChartContent`¶

Field	Type	Description
`tool_use_id`	string	The ID of the tool use that generated this chart
`chart_spec`	string	The vega-lite chart specification serialized as a string

Example

{
  "tool_use_id": "toolu_123",
  "chart_spec": "{\"$schema\":\"https://vega.github.io/schema/vega-lite/v5.json\",\"data\":{...},\"mark\":\"bar\"}"
}

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`CortexAnalystSuggestionDelta`¶

Field	Type	Description
`index`	integer	The index of the suggestion array this delta represents
`delta`	string	The text delta for the suggestion in this index

Example

{
  "index": 0,
  "delta": "What..."
}

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`CortexAnalystToolResultDelta`¶

Field	Type	Description
`text`	string	A text delta from Cortex Analyst’s final response.
`think`	string	A text delta from Cortex Analyst’s reasoning steps.
`sql`	string	A delta from Cortex Analyst’s SQL output. Currently, the entire SQL query comes in a single event but we may stream the SQL token-by-token in the future.
`sql_explanation`	string	A delta from Cortex Analyst’s explanation of what the SQL query does
`query_id`	string	The query id once SQL execution begins
`verified_query_used`	boolean	Whether a verified query was used to generate this response
`result_set`	ResultSet	The results from SQL execution. Matches the schema from Snowflake’s SQL API ResultSet (https://docs.snowflake.cn/en/developer-guide/sql-api/reference#resultset)
`suggestions`	CortexAnalystSuggestionDelta	A delta from Cortex Analyst’s suggested questions. This is sent when Analyst cannot answer the question due to missing information or other failures.

Example

{
  "text": "The...",
  "think": "Thinking...",
  "sql": "SELECT...",
  "sql_explanation": "This...",
  "query_id": "707787a0-a684-4ead-adb0-3c3b62b043d9",
  "verified_query_used": false,
  "result_set": {
    "statementHandle": "707787a0-a684-4ead-adb0-3c3b62b043d9",
    "resultSetMetaData": {
      "partition": 0,
      "numRows": 0,
      "format": "jsonv2",
      "rowType": [
        {
          "name": "my_column",
          "type": "VARCHAR",
          "length": 0,
          "precision": 0,
          "scale": 0,
          "nullable": false
        }
      ]
    },
    "data": [
      [
        "row1 col1",
        "row1 col2"
      ],
      [
        "row2 col1",
        "row2 col2"
      ]
    ]
  },
  "suggestions": {
    "index": 0,
    "delta": "What..."
  }
}

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`ExecutionEnvironment`¶

Configuration for server-executed tools.

Field	Type	Description
`type`	string	The type of execution environment, currently only `warehouse` is supported.
`warehouse`	string	The name of the warehouse (case-sensitive, if it is an unquoted identifier, provide the name in all-caps).
`query_timeout`	integer	The query timeout in seconds

Example

{
  "type": "warehouse",
  "warehouse": "MY_WAREHOUSE",
  "query_timeout": "60"
}

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`Message`¶

Represents a single message in the conversation. Can be either from the user or the assistant.

Field	Type	Description
`role`	string	Identifies who sent the message - either the user or the assistant. User messages typically contain queries, while assistant messages contain responses and tool results.
`content`	array of MessageContentItem	Array of content elements making up the message. Can include text, tool results, or custom content types.

Example

{
  "role": "user",
  "content": [
    {
      "type": "text",
      "text": "What is the total revenue for 2023?"
    }
  ]
}

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`MessageContentItem`¶

Field	Type	Description
`type`	string	The content type (always `chart`).
`chart`	ChartContent	The chart.

Example

{
  "type": "chart",
  "chart": {
    "tool_use_id": "toolu_123",
    "chart_spec": "{\"$schema\":\"https://vega.github.io/schema/vega-lite/v5.json\",\"data\":{...},\"mark\":\"bar\"}"
  }
}

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Field	Type	Description
`type`	string	The content type (always `table`).
`table`	TableContent	The table.

Example

{
  "type": "table",
  "table": {
    "tool_use_id": "toolu_123",
    "query_id": "6ac75378-6337-48a6-80ab-6de48dd680eb",
    "result_set": {
      "statementHandle": "707787a0-a684-4ead-adb0-3c3b62b043d9",
      "resultSetMetaData": {
        "partition": 0,
        "numRows": 0,
        "format": "jsonv2",
        "rowType": [
          {
            "name": "my_column",
            "type": "VARCHAR",
            "length": 0,
            "precision": 0,
            "scale": 0,
            "nullable": false
          }
        ]
      },
      "data": [
        [
          "row1 col1",
          "row1 col2"
        ],
        [
          "row2 col1",
          "row2 col2"
        ]
      ]
    },
    "title": "Revenue by Month"
  }
}

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Field	Type	Description
`text`	string	A text result from the agent
`annotations`	array of Annotation	Any annotations attached to the text result (e.g. citations)
`is_elicitation`	boolean	Whether this text content is the agent asking for more information from the end user.
`type`	string	The content type (always `text`).

Example

{
  "text": "Lorem ipsum dolor...",
  "annotations": [
    {
      "type": "cortex_search_citation",
      "index": 0,
      "search_result_id": "cs_61987ff6-6d56-4695-83c0-1e7cfed818c7",
      "doc_id": "4ac085cb-82d0-4eb4-94f3-2672aa0599a2",
      "doc_title": "Earnings Report",
      "text": "The revenue for 2025 was..."
    }
  ],
  "is_elicitation": false,
  "type": "text"
}

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Field	Type	Description
`type`	string	The content type (always `thinking`).
`thinking`	ThinkingContent	The thinking content.

Example

{
  "type": "thinking",
  "thinking": {
    "text": "To answer your question I must..."
  }
}

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Field	Type	Description
`type`	string	The content type (always `tool_result`).
`tool_result`	ToolResult	The tool result.

Example

{
  "type": "tool_result",
  "tool_result": {
    "tool_use_id": "toolu_123",
    "type": "cortex_analyst_text2sql",
    "name": "my_cortex_analyst_semantic_view",
    "content": [
      {
        "type": "json",
        "json": {
          "answer": 42
        }
      }
    ],
    "status": "success"
  }
}

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Field	Type	Description
`type`	string	The content type (always `tool_use`).
`tool_use`	ToolUse	The tool use.

Example

{
  "type": "tool_use",
  "tool_use": {
    "tool_use_id": "toolu_123",
    "type": "cortex_analyst_text2sql",
    "name": "my_cortex_analyst_semantic_view",
    "input": {
      "location": "San Francisco, CA"
    },
    "client_side_execute": "true"
  }
}

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`ModelConfig`¶

Field	Type	Description
`orchestration`	string	Which LLM to use for orchestration. If left blank, the best LLM available to you will be selected

Example

{
  "orchestration": "claude-4-sonnet"
}

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`ResultSet`¶

Field	Type	Description
`statementHandle`	string	The query id.
`resultSetMetaData`	ResultSetMetaData	Metadata on the result set.
`data`	array of array	2D array representing the data

Example

{
  "statementHandle": "707787a0-a684-4ead-adb0-3c3b62b043d9",
  "resultSetMetaData": {
    "partition": 0,
    "numRows": 0,
    "format": "jsonv2",
    "rowType": [
      {
        "name": "my_column",
        "type": "VARCHAR",
        "length": 0,
        "precision": 0,
        "scale": 0,
        "nullable": false
      }
    ]
  },
  "data": [
    [
      "row1 col1",
      "row1 col2"
    ],
    [
      "row2 col1",
      "row2 col2"
    ]
  ]
}

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`ResultSetMetaData`¶

Field	Type	Description
`partition`	integer	The index number of the partition.
`numRows`	integer	The total number of rows of results.
`format`	string	Format of the data in the result set.
`rowType`	array of RowType	Description of the columns in the result.

Example

{
  "partition": 0,
  "numRows": 0,
  "format": "jsonv2",
  "rowType": [
    {
      "name": "my_column",
      "type": "VARCHAR",
      "length": 0,
      "precision": 0,
      "scale": 0,
      "nullable": false
    }
  ]
}

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`RowType`¶

Field	Type	Description
`name`	string	Name of the column.
`type`	string	Snowflake data type of the column. (https://docs.snowflake.cn/en/sql-reference/intro-summary-data-types)
`length`	integer	Length of the column.
`precision`	integer	Precision of the column.
`scale`	integer	Scale of the column.
`nullable`	boolean	Specifies whether or not the column is nullable.

Example

{
  "name": "my_column",
  "type": "VARCHAR",
  "length": 0,
  "precision": 0,
  "scale": 0,
  "nullable": false
}

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`SqlExplanationToolResultDelta`¶

Field	Type	Description
`text`	string	The text delta for the SQL explanation

Example

{
  "text": "This query selects all columns"
}

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`TableContent`¶

Field	Type	Description
`tool_use_id`	string	The ID of the tool use that generated this table
`query_id`	string	The query id of the sql query that generated this data
`result_set`	ResultSet	The SQL results to render a table. Matches the schema from Snowflake’s SQL API ResultSet (https://docs.snowflake.cn/en/developer-guide/sql-api/reference#resultset)
`title`	string	The title for this table

Example

{
  "tool_use_id": "toolu_123",
  "query_id": "6ac75378-6337-48a6-80ab-6de48dd680eb",
  "result_set": {
    "statementHandle": "707787a0-a684-4ead-adb0-3c3b62b043d9",
    "resultSetMetaData": {
      "partition": 0,
      "numRows": 0,
      "format": "jsonv2",
      "rowType": [
        {
          "name": "my_column",
          "type": "VARCHAR",
          "length": 0,
          "precision": 0,
          "scale": 0,
          "nullable": false
        }
      ]
    },
    "data": [
      [
        "row1 col1",
        "row1 col2"
      ],
      [
        "row2 col1",
        "row2 col2"
      ]
    ]
  },
  "title": "Revenue by Month"
}

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`ThinkingContent`¶

Field	Type	Description
`text`	string	Thinking tokens from the agent

Example

{
  "text": "To answer your question I must..."
}

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`Tool`¶

Defines a tool that can be used by the agent. Tools provide specific capabilities like data analysis, search, or generic functions.

Field	Type	Description
`tool_spec`	ToolSpec	The tool spec

Example

{
  "tool_spec": {
    "type": "generic",
    "name": "get_weather",
    "description": "Fetch the delivery revenue for a location.",
    "input_schema": {
      "type": "object",
      "properties": {
        "location": {
          "type": "string",
          "description": "The city and state, e.g. San Francisco, CA"
        }
      }
    },
    "required": [
      "location"
    ]
  }
}

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`ToolChoice`¶

Field	Type	Description
`type`	string	Determines how tools are selected: - auto - Automatic tool selection (default) - required - Must use at least one tool - tool - Use specific named tools
`name`	array of string	List of specific tool names to use when type is ‘tool’

Example

{
  "type": "auto",
  "name": [
    "analyst_tool",
    "search_tool"
  ]
}

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`ToolInputSchema`¶

Field	Type	Description
`type`	string	The type of the input schema object
`description`	string	A description of what the input is.
`properties`	map of ToolInputSchema	Definitions of each input parameter, if type is `object`
`items`	ToolInputSchema	If type is `array`, the schema for the elements of the array
`required`	array of string	List of required input parameter names, if type is object

Example

{
  "type": "object",
  "description": "Input for my custom tool",
  "properties": {
    "location": {
      "type": "string",
      "description": "The city and state, e.g. San Francisco, CA"
    }
  },
  "items": {},
  "required": [
    "location"
  ]
}

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`ToolResource`¶

Configuration for text-to-SQL analysis tool. Provides parameters for SQL query generation and execution. Exactly one of semantic_model_file, semantic_view or semantic_model_inline must be provided.

Field

Type

Description

semantic_model_file

string

The path to a file stored in a Snowflake Stage holding the semantic model yaml.

semantic_view

string

The name of the Snowflake native semantic model object

semantic_model_inline

string

A semantic model yaml definition

execution_environment

ExecutionEnvironment

Configuration for how to execute the generated SQL query.

Example
{
  "semantic_model_file": "@db.schema.stage/semantic_model.yaml",
  "semantic_view": "db.schema.semantic_view",
  "semantic_model_inline": "name: my_semantic_model ...",
  "execution_environment": {
    "type": "warehouse",
    "warehouse": "MY_WAREHOUSE",
    "query_timeout": "60"
  }
}
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Configuration for search functionality. Defines how document search and retrieval should be performed.

Field

Type

Description

search_service

string

The fully qualified name of the search service.

title_column

string

The title column of the document.

id_column

string

The ID column of the document.

filter

object

Filter query for search results.

Example
{
  "search_service": "database.schema.service_name",
  "title_column": "account_name",
  "id_column": "account_id",
  "filter": {
    "@eq": {
      "<column>": "<value>"
    }
  }
}
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Field

Type

Description

type

string

If the tool is server-side executed, whether it is a Stored Procedure or a UDF.

execution_environment

ExecutionEnvironment

identifier

string

Fully qualified name of the Stored Procedure or UDF

Example
{
  "type": "function",
  "execution_environment": {
    "type": "warehouse",
    "warehouse": "MY_WAREHOUSE",
    "query_timeout": "60"
  },
  "identifier": "MY_DB.MY_SCHEMA.MY_UDF"
}
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Field	Type	Description
`semantic_model_file`	string	The path to a file stored in a Snowflake Stage holding the semantic model yaml.
`semantic_view`	string	The name of the Snowflake native semantic model object
`semantic_model_inline`	string	A semantic model yaml definition
`execution_environment`	ExecutionEnvironment	Configuration for how to execute the generated SQL query.

Field	Type	Description
`search_service`	string	The fully qualified name of the search service.
`title_column`	string	The title column of the document.
`id_column`	string	The ID column of the document.
`filter`	object	Filter query for search results.

Field	Type	Description
`type`	string	If the tool is server-side executed, whether it is a Stored Procedure or a UDF.
`execution_environment`	ExecutionEnvironment
`identifier`	string	Fully qualified name of the Stored Procedure or UDF

`ToolResult`¶

Field	Type	Description
`tool_use_id`	string	Unique identifier for this tool use. Can be used to associated tool results.
`type`	string	The type of the tool (e.g. cortex_search, cortex_analyst_text2sql)
`name`	string	The unique identifier for this tool instance
`content`	array of ToolResultContent	The content on the tool result
`status`	string	The status of tool execution

Example

{
  "tool_use_id": "toolu_123",
  "type": "cortex_analyst_text2sql",
  "name": "my_cortex_analyst_semantic_view",
  "content": [
    {
      "type": "json",
      "json": {
        "answer": 42
      }
    }
  ],
  "status": "success"
}

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`ToolResultContent`¶

Field

Type

Description

type

string

The type of result (always json)

json

object

Structured output from a tool. The schema varies depending on the tool type.

Example
{
  "type": "json",
  "json": {
    "answer": 42
  }
}
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Field

Type

Description

type

string

The type of result (always text)

text

string

The result text

Example
{
  "type": "text",
  "text": "The answer is 42"
}
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Field	Type	Description
`type`	string	The type of result (always `json`)
`json`	object	Structured output from a tool. The schema varies depending on the tool type.

Field	Type	Description
`type`	string	The type of result (always `text`)
`text`	string	The result text

`ToolSpec`¶

Specification of the tool’s type, configuration, and input requirements

Field	Type	Description
`type`	string	The type of tool capability. Can be specialized types like ‘cortex_analyst_text_to_sql’ or ‘generic’ for general-purpose tools.
`name`	string	Unique identifier for referencing this tool instance. Used to match with configuration in tool_resources.
`description`	string	Description of the tool to be considered for tool use
`input_schema`	ToolInputSchema	JSON Schema definition of the expected input parameters for this tool. This will be fed to the Agent so it knows the structure it should follow for when generating the input for ToolUses. Required for generic tools to specify their input parameters.

Example

{
  "type": "generic",
  "name": "get_weather",
  "description": "lorem ipsum",
  "input_schema": {
    "type": "object",
    "properties": {
      "location": {
        "type": "string",
        "description": "The city and state, e.g. San Francisco, CA"
      }
    },
    "required": [
      "location"
    ]
  }
}

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`ToolUse`¶

Field	Type	Description
`tool_use_id`	string	Unique identifier for this tool use. Can be used to associated tool results.
`type`	string	The type of the tool (e.g. cortex_search, cortex_analyst_text2sql)
`name`	string	The unique identifier for this tool instance
`input`	object	The structured input for this tool. The schema of this object should will vary depending on the tool spec.
`client_side_execute`	boolean	Whether the tool use is executed on the client side.

Example

{
  "tool_use_id": "toolu_123",
  "type": "cortex_analyst_text2sql",
  "name": "my_cortex_analyst_semantic_view",
  "input": {
    "location": "San Francisco, CA"
  },
  "client_side_execute": "true"
}

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Cortex Agents Run API¶

Agent run request with agent object¶

Path parameters¶

Request headers¶

Request body¶

Agent run without an agent object¶

Request headers¶

Request body¶

Streaming responses¶

response¶

response.text¶

response.text.delta¶

response.text.annotation¶

response.thinking¶

response.thinking.delta¶

response.tool_use¶

response.tool_result¶

response.tool_result.status¶

response.tool_result.analyst.delta¶

response.tool_result.sql_explanation.delta¶

response.table¶

response.chart¶

response.status¶

error¶

Schemas¶

AgentInstructions¶

Annotation¶

ChartContent¶

CortexAnalystSuggestionDelta¶

CortexAnalystToolResultDelta¶

ExecutionEnvironment¶

Message¶

MessageContentItem¶

ModelConfig¶

ResultSet¶

ResultSetMetaData¶

RowType¶

SqlExplanationToolResultDelta¶

TableContent¶

ThinkingContent¶

Tool¶

ToolChoice¶

ToolInputSchema¶

ToolResource¶

ToolResult¶

ToolResultContent¶

ToolSpec¶

ToolUse¶

`response`¶

`response.text`¶

`response.text.delta`¶

`response.text.annotation`¶

`response.thinking`¶

`response.thinking.delta`¶

`response.tool_use`¶

`response.tool_result`¶

`response.tool_result.status`¶

`response.tool_result.analyst.delta`¶

`response.tool_result.sql_explanation.delta`¶

`response.table`¶

`response.chart`¶

`response.status`¶

`error`¶

`AgentInstructions`¶

`Annotation`¶

`ChartContent`¶

`CortexAnalystSuggestionDelta`¶

`CortexAnalystToolResultDelta`¶

`ExecutionEnvironment`¶

`Message`¶

`MessageContentItem`¶

`ModelConfig`¶

`ResultSet`¶

`ResultSetMetaData`¶

`RowType`¶

`SqlExplanationToolResultDelta`¶

`TableContent`¶

`ThinkingContent`¶

`Tool`¶

`ToolChoice`¶

`ToolInputSchema`¶

`ToolResource`¶

`ToolResult`¶

`ToolResultContent`¶

`ToolSpec`¶

`ToolUse`¶