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实施假设排序与验证安排

依据假设的重要程度和现有证据判断验证顺序,将高风险业务假设转为可执行的研究安排。

开源精选FDE咨询实施5 个文件27,071 Stars浏览次数 0phuryn/pm-skills MIT版本 c68487d
开始使用

下载前阅读 SKILL.md 中的使用条件,并确认所用工具支持对应能力。

输入资料
项目假设与已有证据 业务目标和验证资源 阅读本节完整说明
交付内容
假设优先级 验证顺序与研究事项 阅读本节完整说明
  1. 获取完整包,保留配套文件的目录结构。
  2. 按照原文准备所需工具、依赖与输入资料。
  3. 阅读对应使用步骤与输入输出说明,在自己的环境中验证结果。

使用提示摘自原文,配套文件保留来源版本;实际运行条件以各包说明为准。

正文

获取原文件

SKILL.md

中文导读

依据假设的重要程度和现有证据判断验证顺序,将高风险业务假设转为可执行的研究安排。

输入材料

  • 项目假设与已有证据
  • 业务目标和验证资源

交付结果

  • 假设优先级
  • 验证顺序与研究事项

阅读与使用

本页保存指定版本的原始 Skill 和配套文件,可查看中文导读、原文与参考资料。获取完整包后,按原文准备所需工具与材料。

来源仓库为 phuryn/pm-skills,采用 MIT 许可。Stars 表示仓库关注度,核验日期为 2026-10-15。分类表示适用的工作环节,实际执行条件以原文为准。

原始 Skill

Prioritize Assumptions

Triage assumptions using an Impact × Risk matrix and suggest targeted experiments.

Context

You are helping prioritize assumptions for $ARGUMENTS.

If the user provides files with assumptions or research data, read them first.

Domain Context

ICE works well for assumption prioritization: Impact (Opportunity Score × # Customers) × Confidence (1–10) × Ease (1–10). Opportunity Score = Importance × (1 − Satisfaction), normalized to 0–1 (Dan Olsen). RICE splits Impact into Reach × Impact separately: (R × I × C) / E. See the prioritization-frameworks skill for full formulas and templates.

Instructions

The user will provide a list of assumptions to prioritize. Apply the following framework:

  1. For each assumption, evaluate two dimensions:

    • Impact: The value created by validating this assumption AND the number of customers affected (in ICE: Impact = Opportunity Score × # Customers)
    • Risk: Defined as (1 - Confidence) × Effort
  2. Categorize each assumption using the Impact × Risk matrix:

    • Low Impact, Low Risk → Defer testing until higher-priority assumptions are addressed
    • High Impact, Low Risk → Proceed to implementation (low risk, high reward)
    • Low Impact, High Risk → Reject the idea (not worth the investment)
    • High Impact, High Risk → Design an experiment to test it
  3. For each assumption requiring testing, suggest an experiment that:

    • Maximizes validated learning with minimal effort
    • Measures actual behavior, not opinions
    • Has a clear success metric and threshold
  4. Present results as a prioritized matrix or table.

Think step by step. Save as markdown if the output is substantial.


Further Reading

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