AI Agent Token Budget Planner

The AI Agent Token Budget Planner estimates how many model tokens a single agent task and a full workload will consume. It separates prompt, retrieved context, tool messages, model output, and retry overhead so teams can see which part of an agent loop drives usage.

This planner is useful when sizing API quotas, setting per-task limits, comparing prompt designs, or forecasting monthly demand before deployment. The result includes base tokens per task, adjusted tokens after retries, total workload tokens, and the share used by output generation.

Inputs

tasks
tokens
tokens
tokens
tokens
%
Result
Total token budget
Base tokens per task
Adjusted tokens per task
Retry overhead
Output share

1. Enter workload size
Use the number of agent tasks expected in the planning period.

2. Break down the context
Enter prompt, retrieved context, tool-message, and expected output tokens per task.

3. Allow for retries
Use the retry rate to represent failed runs, validation retries, or agent loops that repeat a model call.

4. Review the budget
Compare adjusted tokens per task with the total workload budget and output-token share.

Base tokens per task = Prompt + Context + Tool messages + Output
Adjusted tokens per task = Base tokens × (1 + Retry rate ÷ 100)
Total token budget = Adjusted tokens per task × Number of tasks

What the result means

The total is the estimated token volume the workload will send to and receive from the model, including retry allowance.

Actual billing can differ because providers may count cached, reasoning, image, or tool-related tokens separately.

Given: 2,500 tasks, 1,000 prompt tokens, 1,600 context tokens, 300 tool-message tokens, 600 output tokens, and a 10% retry rate.

Calculation: Base tokens = 1,000 + 1,600 + 300 + 600 = 3,500. Adjusted tokens = 3,500 × 1.10 = 3,850 per task. Total = 3,850 × 2,500 = 9,625,000 tokens.

Result: Plan for about 9.63 million tokens. The retry allowance contributes 875,000 tokens above the no-retry baseline.

Should system prompts be included?

Yes. Include system and developer instructions in prompt tokens when they are sent on each task.

How should cached tokens be handled?

Enter the full logical token volume here, then apply provider-specific cache discounts separately when estimating cost.

Can retry rate exceed 100%?

Yes. A rate above 100% represents more than one additional attempt per original task on average.

Why separate tool-message tokens?

Tool outputs and function-call payloads can become a large part of the context window and are easier to optimize when tracked separately.

Is this the same as a cost calculator?

No. This planner estimates token volume; a cost calculator also applies input and output prices and any infrastructure charges.