agent-harness-construction

Standardize tool calling schemas by enforcing stable tool naming, schema-first narrow inputs, and deterministic tool output shapes. This ensures consistent message structure across planning, execution, and retries, directly improving agent completion rates and preventing degraded performance from underspecified action spaces.

Observation formatting should standardize outputs to include status, summaries, next actions, and artifact pointers. This structured observation shape provides explicit stop conditions and contextual guidance, enabling the agent to converge efficiently rather than getting stuck in inefficient retry loops.

Design error recovery contracts by defining root-cause hints, safe retry instructions, and explicit stop conditions for each failure path. This structured recovery behavior prevents agents from repeating failed actions blindly and ensures safe, deterministic handling of tool execution errors.

Agent context windows overflow when tool outputs and guidance are inlined directly into prompts. Fix this by applying context budgeting rules: load guidance on demand and reference external files instead of inlining them, keeping the prompt compact throughout the multi-step workflow.

Yes, this approach explicitly applies to ReAct and other tool-using agent workflows where planning, execution, retries, and convergence depend on consistent message structure. Standardizing action spaces and observations ensures the ReAct loop maintains stable reasoning and tool execution.

Avoid deterministic schemas when your workflow requires highly dynamic, unstructured, or free-form tool outputs that cannot be constrained to a predictable shape. If your agent operates without explicit stop conditions or relies on open-ended exploration without context budgeting, this strict standardization may be unnecessary.