agent-harness-construction

Design an AI agent action space by creating stable, explicit tool names and schema-first inputs. This approach ensures deterministic output shapes and improves the agent's planning and tool execution capabilities.

Format AI agent observations by structuring tool responses to include status, summary, next actions, and artifacts. This structured observation content directly enables more efficient agent planning and context budgeting.

Handle API error recovery by defining an error handling contract that includes root cause hints, retry instructions, and stop conditions. This guides the agent to gracefully manage API errors and maintain operational stability.

AI agents often fail interacting with multiple APIs due to poorly defined tool definitions and uninformative responses. Using schema-first inputs and structured observation formatting improves tool usage and completion rates.

You can use structured observation formats for AI agent context budgeting by standardizing tool response shapes. Including status, summary, and artifacts ensures efficient agent operation within limited context windows.

You need schema-first inputs for AI agent tool definitions when creating a new agent that interacts with multiple APIs. This ensures deterministic output shapes and stable tool naming for reliable execution.