Unverified50% confidenceSolutionExact time
Tool call arguments must be parsed via json.loads before they can be accessed, and the arguments output by the model may contain extra characters, missing fields or even invalid JSON, so engineering practice requires wrapping them in try/except and validating required fields.
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50%
Confidence
Long-term
Relevance
10/25/2026
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Related Claims
UnverifiedIn MCP, JSON schema is used to describe tool input parameters; the host can use it to automatically generate call forms, validate parameters or reject invalid parameters in advance, but it does not constrain whether a tool should be called or whether a call is authorized.76% similarUnverifiedWhen selecting a model, the degree of support for Function Calling and JSON Output should be checked as a hard requirement, as support varies greatly across models (some work out of the box, some require fine-tuning, and some do not support it at all).74% similarVerifiedThe Function Calling mechanism allows LLMs to declare in structured JSON format the external tools and parameters they need to invoke, and the tool's return value is injected as-is into the next round of model input.73% similarUnverifiedBy forcing the model to answer using a single tool, you can obtain JSON output that conforms to a schema rather than free-form text that needs to be parsed manually.71% similarUnverifiedAnthropic's Tool Use specification requires clients to declare available tools to the model in JSON Schema format; the model triggers calls via tool_use content blocks, and results are returned in the form of tool_result.71% similar
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