/install decision-matrix
Decision Matrix
Use 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.
Good triggers
- "I need to choose between two job offers — help me decide."
- "Which car should I buy? Evaluate options quantitatively."
- "Decide between renting and buying a home."
- "Compare software vendors for my team."
- "Should I relocate to City A or City B?"
- "Help me make a structured decision about my career path."
Workflow
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List options. Ask the user for 3-5 alternatives. If more than 5, suggest pre-filtering to the top contenders.
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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.
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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.
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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).
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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:
- If the #1 option changes under any ±20% weight shift, flag as unstable
- Report the "stress test" — which criteria cause the most rank volatility
- Identify the tipping point: what weight change would flip rank 1 and 2
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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.
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Deliver decision report. Structure:
- Summary — top-ranked option with total score
- Heatmap table — original scores and weighted totals
- Sensitivity analysis — stability flag, tipping point if any
- Key differentiators — the 1-2 criteria separating the leaders
- Recommendation — ranked list with rationale per option
- Caveats — assumptions made, data gaps, subjective scores flagged
Sample prompt
decision-matrix evaluate --options "Offer A,Offer B,Offer C" --criteria "薪资:8,发展空间:9,稳定性:6"
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install decision-matrix - 安装完成后,直接呼叫该 Skill 的名称或使用
/decision-matrix触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Decision Matrix 是什么?
Multi-factor weighted decision matrix with sensitivity analysis for hard choices. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 21 次。
如何安装 Decision Matrix?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install decision-matrix」即可一键安装,无需额外配置。
Decision Matrix 是免费的吗?
是的,Decision Matrix 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Decision Matrix 支持哪些平台?
Decision Matrix 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Decision Matrix?
由 haidong(@harrylabsj)开发并维护,当前版本 v1.0.0。