reversa-pricing-size

T-shirt sizing for agile features is calculated by analyzing task counts and risk factors like requirement uncertainty. This deterministic formula assigns standardized complexity classes from S to XXL to prevent underestimation during sprint planning.

Deterministic feature sizing is an objective estimation method that uses structural task data and risk adjustments to eliminate ambiguity. It generates standardized size reports by analyzing requirement depth and uncertainty rather than relying on guesswork.

Complexity classes are adjusted by scaling T-shirt sizes based on identified doubts and plan depth. This risk adjustment automatically increases the feature size classification to account for requirement uncertainty and prevent underestimation.

Feature complexity analysis is needed after completing requirements and task breakdown but before roadmap or sprint planning. It provides an objective size estimate to inform scheduling when you have existing task lists and project artifacts ready.

No, this sizing approach requires access to existing requirements, doubts, and task lists to perform multi-factor complexity analysis. It operates on completed project artifacts to generate accurate size calculations.

The best way to estimate structural feature size is using a deterministic T-shirt sizing formula that combines task counts with risk adjustment. This data-driven approach standardizes complexity classes and generates size.json and size.md reports for objective planning.