agent-harness-construction

Design an AI agent action space by defining explicit tool names, bounded input schemas, and deterministic output shapes to ensure deterministic planning and maximize completion reliability.

The best way to format observations for AI agent error recovery is using structured content with status, summary, next_actions, and artifacts to provide a clear recovery contract and safe retry guidance.

Build a robust error recovery contract by defining structured observations and explicit tool definitions that enforce safe retry guidance across exploratory and production-agent tasks.

AI agents fail to select correct tools when lacking explicit tool naming and clear action sequences, which are required to enforce deterministic planning and reliable tool invocation.

Yes, you can apply structured observation formatting with status, summary, next_actions, and artifacts to improve completion rates across exploratory, deterministic, and production-agent tasks.

Yes, bounded input schemas are required to optimize AI agent tool definitions, ensuring deterministic output shapes and reliable action planning across various task environments.