Llama

The current 'direct' reasoning strategy causes ENTITY_006 to fail on complex constraint-satisfaction tasks (like the planning failures seen in dev-suite [1]) because it attempts to solve the problem in a single pass. Switching to 'think_then_answer' will allow the agent to internalize the constraints and simulate the schedule before committing to the final answer, improving planning accuracy without the heavy token overhead of a full separate planner call.

Enabling the planner with a specific prompt focusing on dependency mapping and deadline-backtracking will prevent the agent from greedily scheduling tasks and failing later constraints, as seen in failure [1], without significantly degrading efficiency.

Enabling 'think_then_answer' and 'formatRepair' will prevent the agent from omitting the mandatory ANSWER line and allow it to self-correct constraint violations (like word counts or specific word placements) before final output.

Switching the reasoning strategy from 'direct' to 'plan_and_execute' and enabling a structured planner will prevent off-by-one errors in multi-step reasoning tasks (like the robot work-cycle problem) by forcing the agent to explicitly map out the sequence of events before calculating the final date.