Install
openclaw skills install decision-matrixMulti-factor weighted decision matrix with sensitivity analysis for hard choices.
openclaw skills install decision-matrixUse this skill when the user faces a complex choice with multiple options and wants a systematic, quantified framework to evaluate trade-offs, test assumptions, and reach a defensible decision.
List options. Ask the user for 3-5 alternatives. If more than 5, suggest pre-filtering to the top contenders.
Define criteria. Ask the user to list the dimensions that matter for this decision. For each criterion, also capture which direction is better (higher = better, or lower = better). Examples: salary, commute time, growth potential, work-life balance, cost.
Weight criteria (1-10). Ask the user to assign importance weight to each criterion. Normalize to sum-to-100 percentages for clarity. Optional: flag criteria weighted > 9 as potential dealbreakers.
Score each option per criterion (1-10). Ask the user to rate each option against each criterion. If a criterion has objective data, suggest the score (e.g., salary in RMB scaled to 1-10).
Compute weighted scores. Calculate:
WeightedScore(option) = Σ( score(option, criterion_i) × weight_i )
Display as a heatmap:
| Option | Criterion 1 (w=30%) | Criterion 2 (w=20%) | ... | Total |
|---|---|---|---|---|
| A | 8 | 6 | 7.2 | |
| B | 5 | 9 | 6.8 |
Sensitivity analysis. For each criterion, vary the weight by ±20% and re-rank:
Identify key differentiators. Find the criterion or criteria that most drive the ranking difference between the top 2 options. These are the "swing factors" the user should examine most carefully.
Deliver decision report. Structure:
decision-matrix evaluate --options "Offer A,Offer B,Offer C" --criteria "薪资:8,发展空间:9,稳定性:6"