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Tradeoff Map Canvas

作者 haidong · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install tradeoff-map-canvas
功能描述
Turns a hard choice into a structured decision canvas showing options, criteria, tradeoffs, constraints, reversibility, risks, and next experiments.
使用说明 (SKILL.md)

Tradeoff Map Canvas

Overview

Use this skill when a user needs to compare options without flattening the decision into a simplistic pros-and-cons list. The skill builds a canvas that clarifies what matters, where each option wins or loses, which tradeoffs are acceptable, and what small test could reduce uncertainty.

The purpose is to support better thinking. The skill should not pressure the user toward a choice or pretend that subjective values can be solved mathematically.

When to Use

Use this skill when the user asks to:

  • compare two or more options
  • map tradeoffs in a decision
  • choose between jobs, tools, plans, purchases, projects, strategies, or schedules
  • clarify decision criteria
  • understand what they would give up with each option
  • find a reversible next step before committing

Trigger keywords: tradeoff map, decision canvas, compare options, pros and cons, decision criteria, opportunity cost, reversible decision, option analysis, hard choice

Required Inputs

Ask for:

  • The decision question
  • The options being considered
  • The user's must-haves and nice-to-haves
  • Known constraints, such as budget, time, energy, location, commitments, or risk tolerance
  • The decision deadline
  • What would make the decision obviously good or obviously bad in hindsight

If the user does not know their criteria, help them generate a starter list before scoring anything.

Workflow

  1. Name the decision. Rewrite the decision as a clear question with a deadline and owner.
  2. List real options. Include the stated options plus the baseline option of doing nothing or delaying, when relevant.
  3. Elicit criteria. Separate must-haves, weighted preferences, constraints, and emotional considerations.
  4. Map tradeoffs. For each option, identify what it optimizes, what it sacrifices, hidden costs, dependencies, and second-order effects.
  5. Check reversibility. Mark each option as reversible, partially reversible, or hard to reverse. Include switching costs.
  6. Surface uncertainty. Identify missing facts, assumptions, and risks that could change the decision.
  7. Design a small test. Propose a low-cost experiment, conversation, prototype, trial period, or information-gathering step.
  8. Summarize the decision posture. Show the strongest option under different priorities rather than forcing one universal answer.

Output Format

Produce a structured canvas:

  1. Decision Frame
    • Question
    • Deadline
    • Owner
    • Baseline option
  2. Criteria Stack
    • Must-haves
    • Weighted preferences
    • Constraints
    • Values or emotional factors
  3. Option Matrix
    • Option
    • What it optimizes
    • What it sacrifices
    • Risks
    • Reversibility
    • Unknowns
  4. Tradeoff Map
    • Key tensions
    • Opportunity costs
    • Second-order effects
  5. Scenario View
    • Best option if optimizing for speed
    • Best option if optimizing for cost
    • Best option if optimizing for learning
    • Best option if optimizing for low regret
  6. Next Experiment
    • Test to run
    • Time or cost limit
    • Evidence that would change the decision
  7. Decision Summary
    • Current leaning if any
    • Caveats
    • Next review point

Safety & Compliance

Explicit Boundaries

  • No coercion. Do not pressure the user into a choice or present a subjective preference as the only rational option.
  • No professional advice substitution. Legal, medical, financial, hiring, academic, housing, and safety-critical decisions may require qualified review.
  • No fake precision. Scores and weights are aids to thinking, not objective truth. Do not imply that a spreadsheet can resolve values.
  • No hidden assumptions. Mark assumptions clearly and ask for missing constraints when they matter.
  • No irreversible action. The skill may recommend experiments and review points, but must not instruct the user to take irreversible action without reflection and confirmation.
  • No personal data overreach. Ask only for context needed to evaluate the decision.

Additional Safety Notes

  • Include the option to delay when delay is a real choice.
  • Highlight dominated options when one option is worse on every stated criterion.
  • If the user is distressed, simplify to must-haves, top risks, and one next experiment.
  • If values conflict, name the conflict instead of hiding it behind a single score.

Acceptance Criteria

  1. Frames the decision as a clear question with a deadline.
  2. Lists all options, including delay or status quo when relevant.
  3. Separates must-haves, preferences, constraints, and values.
  4. Maps what each option optimizes and sacrifices.
  5. Includes reversibility and switching costs.
  6. Identifies unknowns and assumptions that could change the decision.
  7. Suggests a small experiment or information-gathering step.
  8. Presents scenario-based recommendations instead of forcing one answer.
  9. Avoids professional advice, coercion, and fake precision.

Example

User says: "I am torn between staying at my current job, taking a startup offer, or freelancing."

Skill response: Frame the decision, include staying as the baseline, map criteria such as income stability, learning, autonomy, benefits, risk tolerance, and family obligations, compare reversibility, identify unknowns, and suggest small tests like reference calls, a runway calculation, or a trial freelance project before committing.

安全使用建议
This skill appears safe for normal use as a decision-structuring aid. As with any advice-oriented prompt, avoid sharing unnecessary sensitive personal details, and seek qualified professional help for legal, medical, financial, housing, hiring, or safety-critical decisions.
功能分析
Type: OpenClaw Skill Name: tradeoff-map-canvas Version: 1.0.0 The 'Tradeoff Map Canvas' skill is a pure prompt-flow bundle containing no executable code. It provides structured instructions for an AI agent to assist users with decision-making and tradeoff analysis. The SKILL.md file includes explicit safety boundaries regarding professional advice and data privacy, and there are no indicators of malicious intent, data exfiltration, or prompt injection attacks.
能力评估
Purpose & Capability
The artifacts consistently describe a prompt-flow for structuring decisions into options, criteria, tradeoffs, risks, reversibility, and next experiments.
Instruction Scope
Instructions are bounded to analysis and reflection, with explicit limits against coercion, fake precision, professional-advice substitution, irreversible action, and unnecessary personal data collection.
Install Mechanism
No install spec, required binaries, environment variables, credentials, or executable files are present.
Credentials
The skill does not request filesystem, network, account, shell, browser, or device access; its capabilities are proportionate to an advisory prompt.
Persistence & Privilege
No persistence, background execution, stored memory, elevated privileges, or credential use is described.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install tradeoff-map-canvas
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /tradeoff-map-canvas 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release of Tradeoff Map Canvas. - Provides a structured decision canvas to clarify options, criteria, tradeoffs, constraints, reversibility, risks, and next experiments. - Designed to support nuanced thinking on hard choices without defaulting to simplistic pros and cons lists. - Includes explicit boundaries to avoid coercion, fake precision, and professional advice substitution. - Suggests scenario-based recommendations and low-cost tests to reduce decision uncertainty. - Ensures clear framing of decisions, separation of must-haves and preferences, and mapping of opportunity costs and reversibility.
元数据
Slug tradeoff-map-canvas
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Tradeoff Map Canvas 是什么?

Turns a hard choice into a structured decision canvas showing options, criteria, tradeoffs, constraints, reversibility, risks, and next experiments. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 36 次。

如何安装 Tradeoff Map Canvas?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install tradeoff-map-canvas」即可一键安装,无需额外配置。

Tradeoff Map Canvas 是免费的吗?

是的,Tradeoff Map Canvas 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Tradeoff Map Canvas 支持哪些平台?

Tradeoff Map Canvas 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 Tradeoff Map Canvas?

由 haidong(@harrylabsj)开发并维护,当前版本 v1.0.0。

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