agentscope-ai/agentscope · error · ValueError

Invalid input_schema

Error message

Invalid input_schema: {self.tool.input_schema}.

What it means

ToolMetadata's __post_init__ validates that a tool's input_schema, if provided, is a JSON-Schema object of type 'object' with a dict 'properties' entry — the shape OpenAI-style function-calling APIs require. Anything else (missing 'type', non-dict, wrong type value) is rejected.

Solutions

  1. Make the schema a dict literal like {'type': 'object', 'properties': {...}}
  2. If generating from pydantic, use Model.model_json_schema() and ensure the top level is an object schema (it normally is)
  3. Pass None instead of {} if the tool takes no arguments

Example fix

# before
tool = Tool(name='t', input_schema='{"type": "object"}')  # string, not dict
# after
tool = Tool(name='t', input_schema={'type': 'object', 'properties': {'x': {'type': 'string'}}})
Defensive patterns

Strategy: validation

Validate before calling

def is_valid_tool_schema(s) -> bool:
    return s is None or (isinstance(s, dict) and s.get('type') == 'object' and isinstance(s.get('properties'), dict))

assert is_valid_tool_schema(schema)

Type guard

def is_valid_tool_schema(s) -> bool:
    return s is None or (isinstance(s, dict) and s.get('type') == 'object' and isinstance(s.get('properties'), dict))

Prevention

When it happens

Trigger: Setting tool input_schema to a non-dict, a schema without {'type': 'object'}, or where 'properties' is not a dict — e.g. passing a pydantic model's model_json_schema() result whose top level is not an object schema, or a list/JSON string.

Common situations: Hand-writing schemas and omitting 'type': 'object'; passing a JSON string instead of a parsed dict; wrapping the schema in {'parameters': ...} or {'schema': ...} by mistake; schema versions that emit 'properties' differently.

Understand the failure class

Background: Schema validation failed / invalid input schema: payload rejected because its shape doesn't match the expected schema — this error's family across 28 libraries.

Related errors

AI-assisted analysis of agentscope-ai/agentscope@e90f1c7592 (2026-08-28). Data as JSON: /api/errors/97bee79ae3579114. Report an issue: GitHub.

Appendix: source

Thrown at src/agentscope/tool/_types.py:52

    """The base model used to extend the JSON schema of the original tool
    function, so that we can dynamically adjust the tool function."""

    # Tools management fields
    group: str | Literal["basic"] = "basic"
    """The belonging group of the tool function"""
    original_name: str | None = field(default=None)
    """The original name of the tool function when it has been renamed."""

    def __post_init__(self) -> None:
        """Validate the registered tool function after initialization."""
        # validate schema
        if self.tool.input_schema is not None:
            if not (
                isinstance(self.tool.input_schema, dict)
                and self.tool.input_schema.get("type") == "object"
                and isinstance(self.tool.input_schema.get("properties"), dict)
            ):
                raise ValueError(
                    f"Invalid input_schema: {self.tool.input_schema}. ",
                )

    def get_tool_schema(
        self,
        extended_model: Type[BaseModel] | None = None,
    ) -> dict:
        """Get the JSON schema of the tool function via the following steps:

        1. Remove preset_kwargs from the JSON schema, since they are not
        exposed to the agent.
        2. If extended_model is provided, merge its schema with the
        current function schema.

        Args:
            extended_model (`Type[BaseModel] | None`, optional):
                The dynamic BaseModel used to extend the original function. If
                provided, the given BaseModel will be merged into the original

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