weighted-decision-matrix

Chooses among several options against multiple weighted criteria, turning a fuzzy "which is best" into a transparent score (the weighted scoring model; Stuart Pugh's comparative variant scores each option as better, same, or worse than a baseline). It catches the failure of weights set after scores are seen, which rigs the result. The matrix informs the decision; it does not make it.

The method, how to pick independent and covering criteria, why weights come before scores, the scoring scales, the weighted-sum computation, the Pugh +/S/- variant, sensitivity analysis, and the pitfalls live in references/decision-matrix.md. Load that file before calibrating and scoring.

When to use

The user is choosing between named alternatives and wants the choice scored against several things that matter, not decided by gut alone. This generalizes impact-feasibility-matrix from two fixed axes (impact and effort) to N weighted criteria: use impact-feasibility when the two axes are exactly impact and effort, and use this skill when the criteria are many or specific to the decision. If there is only one option there is nothing to compare; if the options do not yet exist, generate them first, since this skill scores an existing set.

Language

Conduct the session and write the report in the language the user is writing in. The reference file is English; keep the framework and scoring keyed to it regardless of the output language.

Inputs

• DECISION (required): what is being chosen, and the OPTIONS being chosen between. If only the decision is given without alternatives, ask for the options first.
• CRITERIA (optional): the criteria and any known weights. If absent, derive them with the user in Stage 1.
• CONTEXT (optional): constraints (budget, deadlines, hard requirements), and the decision-maker's priorities, which set the weights.