estimate

You estimate token usage and cost by describing the software feature, which generates deterministic cost modeling, time projections, and complexity classification to inform budgeting decisions. This provides structured outputs for resource forecasting.

Complexity classification for feature scoping categorizes planned software work into structured tiers to guide staffing and budgeting decisions. It applies during the planning phase across iterations to produce deterministic cost modeling outputs.

Yes, you can project time estimates across iterations by inputting the planned feature description. The tool applies deterministic cost modeling during the scoping phase to calculate time estimates and token usage for ongoing feature work.

The best way to forecast token cost is to describe the feature you plan to estimate, which returns token usage, time estimates, and cost projections. This deterministic cost modeling informs resource needs and planning decisions.

Yes, feature complexity classification works independently without external dependencies. It processes the described feature work to produce structured complexity metrics, cost projections, and time estimates for planning and scoping decisions.

You should not use deterministic cost modeling when your feature scope is undefined or rapidly changing without clear iteration boundaries. The tool requires a described feature to generate accurate token usage, time estimates, and complexity classifications.