Structured output

For the full guide, see Structured output.

Basic extraction

Provide an output_schema and the agent will extract validated JSON after the agentic loop completes.

rkat run --output-schema '{
  "type": "object",
  "properties": {
    "city": {"type": "string"},
    "country": {"type": "string"},
    "population": {"type": "integer"}
  },
  "required": ["city", "country", "population"]
}' "Tell me about Tokyo"

{
  "jsonrpc": "2.0", "id": 1,
  "method": "session/create",
  "params": {
    "prompt": "Tell me about Tokyo",
    "output_schema": {
      "type": "object",
      "properties": {
        "city": {"type": "string"},
        "country": {"type": "string"},
        "population": {"type": "integer"}
      },
      "required": ["city", "country", "population"]
    }
  }
}

curl -X POST http://localhost:8080/sessions \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Tell me about Tokyo",
    "output_schema": {
      "type": "object",
      "properties": {
        "city": {"type": "string"},
        "country": {"type": "string"},
        "population": {"type": "integer"}
      },
      "required": ["city", "country", "population"]
    }
  }'

{
  "prompt": "Tell me about Tokyo",
  "output_schema": {
    "type": "object",
    "properties": {
      "city": {"type": "string"},
      "country": {"type": "string"},
      "population": {"type": "integer"}
    },
    "required": ["city", "country", "population"]
  }
}

Called via the meerkat_run tool.

session = await client.create_session(
    "Tell me about Tokyo",
    output_schema={
        "type": "object",
        "properties": {
            "city": {"type": "string"},
            "country": {"type": "string"},
            "population": {"type": "integer"},
        },
        "required": ["city", "country", "population"],
    },
)
print(session.structured_output)

const session = await client.createSession("Tell me about Tokyo", {
  outputSchema: {
    type: "object",
    properties: {
      city: { type: "string" },
      country: { type: "string" },
      population: { type: "integer" },
    },
    required: ["city", "country", "population"],
  },
});
console.log(session.structuredOutput);

let schema = OutputSchema::new(json!({
    "type": "object",
    "properties": {
        "city": {"type": "string"},
        "country": {"type": "string"},
        "population": {"type": "integer"}
    },
    "required": ["city", "country", "population"]
}))?;

let result = service.create_session(CreateSessionRequest {
    model: "claude-sonnet-4-5".into(),
    prompt: "Tell me about Tokyo".into(),
    system_prompt: None,
    max_tokens: None,
    event_tx: None,
    skill_references: None,
    initial_turn: InitialTurnPolicy::RunImmediately,
    build: Some(SessionBuildOptions {
        output_schema: Some(schema),
        ..Default::default()
    }),
    labels: None,
}).await?;
println!("{:?}", result.structured_output);

Schema from file

The CLI can load a schema from a JSON file instead of inline.

rkat run --output-schema ./schemas/city.json "Tell me about Tokyo"

The CLI detects files by checking if the value is an existing path. The file can contain a raw JSON Schema or the wrapper format with explicit name, strict, compat, and format fields.

Retries

When validation fails, the agent retries the extraction turn with error feedback. The default is 2 retries (3 total attempts).

rkat run --output-schema ./schema.json --structured-output-retries 5 "Extract entities"

{
  "jsonrpc": "2.0", "id": 2,
  "method": "session/create",
  "params": {
    "prompt": "Extract entities",
    "output_schema": {"type": "object", "properties": {"entities": {"type": "array"}}},
    "structured_output_retries": 5
  }
}

curl -X POST http://localhost:8080/sessions \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Extract entities",
    "output_schema": {
      "type": "object",
      "properties": {"entities": {"type": "array"}},
      "required": ["entities"]
    },
    "structured_output_retries": 5
  }'

{
  "prompt": "Extract entities",
  "output_schema": {
    "type": "object",
    "properties": {"entities": {"type": "array"}},
    "required": ["entities"]
  },
  "structured_output_retries": 5
}

Called via the meerkat_run tool.

session = await client.create_session(
    "Extract entities",
    output_schema={"type": "object", "properties": {"entities": {"type": "array"}}},
    structured_output_retries=5,
)

const session = await client.createSession("Extract entities", {
  outputSchema: { type: "object", properties: { entities: { type: "array" } } },
  structuredOutputRetries: 5,
});

let result = service.create_session(CreateSessionRequest {
    model: "claude-sonnet-4-5".into(),
    prompt: "Extract entities".into(),
    system_prompt: None,
    max_tokens: None,
    event_tx: None,
    skill_references: None,
    initial_turn: InitialTurnPolicy::RunImmediately,
    build: Some(SessionBuildOptions {
        output_schema: Some(schema),
        structured_output_retries: 5,
        ..Default::default()
    }),
    labels: None,
}).await?;

Compatibility mode

Schemas are normalized across providers. The compat setting controls how unsupported JSON Schema features are handled during provider-specific lowering.

# Lossy (default): unsupported features are dropped with warnings
rkat run --output-schema ./schema.json --output-schema-compat lossy "Extract data"

# Strict: reject schemas with unsupported features
rkat run --output-schema ./schema.json --output-schema-compat strict "Extract data"

Mode	Behavior
`lossy`	Best-effort lowering; unsupported features are dropped with warnings
`strict`	Reject schemas with unsupported features for the target provider

Warnings are included in the response as schema_warnings. The same schema works with Anthropic, OpenAI, and Gemini — provider-specific lowering is handled transparently.

Read the result

The structured output appears in the response alongside the raw text.

# --output json returns the full result including structured_output
rkat run --output json --output-schema '{"type":"object","properties":{"answer":{"type":"string"}},"required":["answer"]}' "What is 2+2?"
# stdout: {"session_id":"...","text":"...","structured_output":{"answer":"4"}}

{
  "jsonrpc": "2.0", "id": 1,
  "result": {
    "session_id": "01936f8a-...",
    "text": "{\"city\":\"Tokyo\",\"country\":\"Japan\",\"population\":13960000}",
    "structured_output": {
      "city": "Tokyo",
      "country": "Japan",
      "population": 13960000
    },
    "schema_warnings": [],
    "turns": 2,
    "tool_calls": 0,
    "usage": {"input_tokens": 120, "output_tokens": 45, "total_tokens": 165}
  }
}

{
  "session_id": "01936f8a-...",
  "text": "{\"city\":\"Tokyo\",\"country\":\"Japan\",\"population\":13960000}",
  "structured_output": {
    "city": "Tokyo",
    "country": "Japan",
    "population": 13960000
  },
  "schema_warnings": [],
  "turns": 2,
  "tool_calls": 0,
  "usage": {"input_tokens": 120, "output_tokens": 45, "total_tokens": 165}
}

// meerkat_run response includes structured_output in the tool result
{
  "content": [{"type": "text", "text": "{\"session_id\":\"...\",\"structured_output\":{\"answer\":\"4\"}}"}]
}

session = await client.create_session("Tell me about Tokyo", output_schema=schema)
data = session.structured_output  # dict: {"city": "Tokyo", "country": "Japan", ...}
print(data["city"])
print(data["population"])

const session = await client.createSession("Tell me about Tokyo", { outputSchema: schema });
const data = session.structuredOutput;  // { city: "Tokyo", country: "Japan", ... }
console.log(data.city);
console.log(data.population);

let result = service.create_session(req).await?;
if let Some(output) = &result.structured_output {
    let city = output["city"].as_str().unwrap_or_default();
    let pop = output["population"].as_i64().unwrap_or_default();
    println!("{}: {}", city, pop);
}

if let Some(warnings) = &result.schema_warnings {
    for w in warnings {
        eprintln!("{:?} at {}: {}", w.provider, w.path, w.message);
    }
}

Getting started

Core concepts

Guides

Examples

Structured output

Basic extraction

Schema from file

Retries

Compatibility mode

Read the result

Getting started

Core concepts

Guides

Examples

​Basic extraction

​Schema from file

​Retries

​Compatibility mode

​Read the result

Basic extraction

Schema from file

Retries

Compatibility mode

Read the result