Output Validation
An independent validation layer in AI agent error handling that intercepts substandard outputs before they enter the reasoning chain, using methods such as JSON Schema structural validation, required field checks, numeric range verification, and semantic consistency checks.
Timeline (last 90 days)
Output validation strategies cover format validation, content filtering, factual verification, reasoning chain review, consistency checking, and style compliance.
Output validation is an independent check layer between "call succeeded" and "task succeeded," and commonly used methods include JSON Schema validation, required-field checks, numeric range checks, date expiry checks, and consistency checks against user constraints.
All Facts (2)
Output validation strategies cover format validation, content filtering, factual verification, reasoning chain review, consistency checking, and style compliance.
50%UnverifiedOutput validation is an independent check layer between "call succeeded" and "task succeeded," and commonly used methods include JSON Schema validation, required-field checks, numeric range checks, date expiry checks, and consistency checks against user constraints.
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