df:list-objective-assumptions

To validate planning assumptions, you analyze a specific objective to surface Claude's assumptions about technical approach, scope, risks, and dependencies. This diagnostic process highlights misalignments against your current roadmap and project state before you proceed.

Objective assumption analysis is a diagnostic technique that exposes AI planning assumptions regarding implementation order and scope boundaries. You need it before proceeding with workflow planning to ensure technical feasibility and identify hidden risks early.

Yes, you can check objective feasibility by applying the objective to your current project state and roadmap. This validates the proposed technical approach and highlights any misalignments or dependency conflicts before you commit to planning.

You surface scope boundaries and technical risks by running a diagnostic analysis on the objective. This extracts Claude's implicit assumptions about dependencies, implementation order, and risk areas, presenting them in a clear, actionable output for your review.

No, this workflow planning diagnostic requires no external dependencies or components. You simply provide the objective number to analyze and surface Claude's planning assumptions directly within your current environment.

After the objective analysis surfaces planning assumptions and misalignments, the output ends with a prompt asking for your feedback to decide next steps. You review the highlighted risks and scope boundaries to determine whether to proceed or adjust.