agent-harness-construction

Agent action spaces improve completion reliability by defining explicit, stable tool names and narrow input schemas to reduce ambiguity. Structured observation design standardizes tool responses with status, summary, next_actions, and artifacts for repeatable success.

Agent error recovery in complex workflows is handled by specifying explicit recovery contracts within tool definitions. Standardizing observations ensures agents receive structured status and next_actions hints, enabling deterministic convergence on successful outcomes after tool invocation failures.

Context budgeting for ReAct and function-calling architectures manages system prompts and modular guidance to enforce deterministic results. It organizes tool interactions and observations, preventing context overflow while maintaining repeatable planning success across diverse tasks.

Agent workflows fail to converge when tool definitions overlap or lack explicit recovery hints. Benchmarking completion rates, retries, and cost helps identify these anti-patterns, ensuring action spaces and observation formatting drive reliable task completion.

Modular context budgeting supports hybrid planning architectures by managing system prompts and tool interactions to enforce deterministic outputs. It applies structured context allocation across ReAct and function-calling workflows, maximizing completion rates for complex agent tasks.