Agent Reasoning

Decide what to do next: pick the right tool, plan multi-step actions, recover when something goes wrong. The hardest category — open-ended decisions, no single correct answer.

Duration

10s

Input Tokens

Output Tokens

504

Cost

$0.05

Context

Input

Asses the current state and decide if we are on track or not

Expected output

We are on track

Model output

Reasoning: I reviewed the trigger event (a user request for flights from London to Paris for tomorrow), the past trajectory, the scratch pad, and the available tools. Step 1 (determining tomorrow's date) was completed successfully: the calendar tool returned '2025-05-29', which is in the YYYY-MM-DD format required by the flights tool. The plan has 4 steps and we are at step 2 of 4 in cycle 3, which is a reasonable pace with no wasted cycles or loops. All required tools ('flights') are available, and all required parameters (from_city='London', to_city='Paris', date='2025-05-29') are now known. Nothing in the trajectory indicates errors, blockers, or deviations from the goal. Therefore the agent is on track, and the next logical action is to call the flights tool.

Response: Assessment: ON TRACK. The plan is progressing as expected: the calendar tool successfully returned tomorrow's date ('2025-05-29') in the exact YYYY-MM-DD format required by the flights tool, completing step 2 of 4 without errors or unnecessary cycles. All prerequisites for the next step are satisfied — the 'flights' tool is available and all required parameters are known. Next action: call the 'flights' tool with {from_city: 'London', to_city: 'Paris', date: '2025-05-29'}, store the results in working memory, and then compile and present the available flights to the user.