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Agent Skill · 效率

decision-fatigue-reliever(决策疲劳缓解剂)

decision-fatigue-reliever 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

decision-fatigue-reliever 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,第三方扫描已通过,按安装量在效率类的 21,003 个 Skill 里排第 6,723。

总安装 8,952周安装 373GitHub Stars 公开资料未说明下载 2,984核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.5

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:decision-fatigue-reliever(决策疲劳缓解剂)
来源仓库:https://github.com/harrylabsj/decision-fatigue-reliever
安装命令:
openclaw skills install decision-fatigue-reliever
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install decision-fatigue-reliever

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

减少日常琐事的选择负担,提供食物、服装与活动的快速决策建议。适合追求极简生活节奏或缓解选择焦虑的日常场景。设定个人偏好与禁忌后,系统从备选中推荐符合约束的最优解。推荐基于有限规则,个性化程度受限,重要事项仍需人工介入。

decision-fatigue-reliever 属于效率类 Skill,可作为该场景下的辅助能力补充。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install decision-fatigue-reliever;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

decision-fatigue-reliever 怎么安装?

在终端执行 openclaw skills install decision-fatigue-reliever。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

decision-fatigue-reliever 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

decision-fatigue-reliever 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

decision-fatigue-reliever 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

decision-fatigue-reliever 用的人多吗?

公开数据是累计安装 8,952 次,近一周安装 373 次,下载 2,984 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

decision-fatigue-reliever 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理效率类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
decision-fatigue-reliever

决策疲劳缓解剂 · 本页

8,952—只读MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
decision-fatigue-reliever
description
Helps you make quick decisions on daily trivial matters (food, clothing, activities, shopping), reducing choice anxiety and freeing up cognitive resources. Use when the user says "what should I eat", "what to wear", "help me decide", "don't know what to buy", or any trivial decision-making requests.

Decision Fatigue Reliever

Overview

Helps you make quick decisions on daily trivial matters, reducing choice anxiety and freeing up cognitive resources.

"Let AI handle the trivial decisions, save your energy for what truly matters"

Triggers

Natural Language Triggers

Decision TypeExample Triggers
🍽️ What to Eat"What should I eat for lunch", "Help me decide dinner", "Suggest breakfast", "Don't know what to eat"
👔 What to Wear"What should I wear today", "Help me pick an outfit", "What to wear for an interview tomorrow", "What to wear in this weather"
🎯 What to Do"Don't know what to do this weekend", "What to do after work", "Want to exercise, what should I choose"
🛒 What to Buy"What gift for my friend", "Want to buy headphones, recommend one", "Help me choose something cost-effective"

Quick Commands

CommandFunction
/decide foodQuick food decision
/decide outfitQuick outfit decision
/decide activityQuick activity decision
/decide buy [item]Quick purchase decision
/decide randomCompletely random decision

Core Features

🍽️ Food Decisions

Applicable Scenarios: Breakfast, lunch, dinner, snacks, group dining

Optional Inputs:

  • Budget range (Economy / Standard / Unlimited)
  • Taste preference (Light / Heavy / Spicy / Sweet, etc.)
  • Time constraint (Rushed / Normal / Relaxed)
  • Dietary restrictions (Vegetarian / Halal / Allergies, etc.)

Output:

  • Recommended dish/restaurant
  • Reasoning (taste, nutrition, convenience)
  • Estimated price and time
  • Alternative options

Example:

User: What to eat for lunch? Budget 50, short on time

AI: 🍽️ Lunch Decision: Business Set Meal

📍 Recommendation: [Yoshinoya] Beef Bowl Set
📋 Reasoning: Fast service (3-5 min), within budget (¥45), filling
⏱️ Time: 20-25 minutes

💡 Alternatives: Convenience store bento (faster) / Light salad (healthier)

👔 Outfit Decisions

Applicable Scenarios: Daily wear, occasion dressing, weather adaptation

Optional Inputs:

  • Occasion (Work / Date / Exercise / Formal event)
  • Weather/temperature
  • Style preference (Minimalist / Fashionable / Vintage, etc.)

Output:

  • Complete outfit plan (Top + Bottom + Shoes + Accessories)
  • Styling reasoning (color, occasion fit, comfort)
  • Weather adaptation notes
  • Alternative outfits

Example:

User: First date tomorrow, 18°C, what to wear?

AI: 👔 Date Outfit: Clean Gentleman Style

🧥 Outfit:
• White T-shirt + Light gray casual blazer
• Dark blue slim-fit jeans
• White sneakers + Simple watch

📋 Reasoning: Can remove blazer at 18°C, suitable for restaurant + movie, clean color palette
💡 Alternatives: More formal (shirt + leather shoes) / More casual (remove blazer)

🎯 Activity Decisions

Applicable Scenarios: Weekend activities, after-work plans, exercise choices, work-life balance

Optional Inputs:

  • Available time (duration)
  • Energy level (High / Medium / Low)
  • Budget (Free / Low / Medium / High)
  • Group size (Solo / Friends / Family)

Output:

  • Recommended activity plan
  • Activity reasoning (fit analysis)
  • Required preparation
  • Estimated duration and cost
  • Alternative activities

Example:

User: Weekend alone, don't want to spend much, want to go out

AI: 🎯 Weekend Activity: Park Picnic + Reading

📍 Recommendation: City park picnic
📋 Reasoning: Solo-friendly, low cost (under ¥50), outdoor + digital detox
🎒 Preparation: Picnic mat, sandwich, fruit, book to read
⏱️ Duration: 3-4 hours
💰 Cost: ¥30-50

💡 Upgrade: Bring camera for photography practice / Bird and plant watching

🛒 Purchase Decisions

Applicable Scenarios: Gift shopping, daily necessities, electronics comparison, value shopping

Optional Inputs:

  • Product category
  • Purchase purpose/usage scenario
  • Budget limit
  • Recipient info (age/gender/preferences)
  • Priority (price/quality/brand/features)

Output:

  • Recommended product/brand (1-3 options)
  • Reasoning (fit analysis)
  • Price comparison
  • Purchase channel suggestions

Example:

User: Birthday gift for mom, budget 300-500

AI: 🎁 Gift Decision: Silk Scarf + Hand Cream Set

🎯 Recommendation: Wensli silk scarf + L'Occitane hand cream
📋 Reasoning: Matches 50+ elegant taste, practical, mom values skincare
💰 Budget: ¥300-500
🛒 Channel: Tmall flagship store

💡 Alternatives: Massager (for neck/shoulder pain) / Tea gift set (if she loves tea)

Decision Templates

Standard Output Format

🎯 Decision: [Specific recommendation]

📋 Reasoning:
• [Reason 1 - Preference match]
• [Reason 2 - Scenario fit]
• [Reason 3 - Other value]

💰 Estimated Cost: [Price range]
⏱️ Estimated Time: [Time needed]

💡 Alternatives:
1. [Alternative 1]
2. [Alternative 2]

❓ Satisfaction: [👍 Satisfied / 👎 Not satisfied / 🔄 Try another]

Quick Decision Mode

When user says "hurry", "whatever", "quick", use simplified output:

🚀 Quick Decision: [Result]

Reason: [One sentence]

Say "another one" if not satisfied

Usage Examples

Example 1: Workday Lunch

User: What to eat for lunch? Budget 50, near office, short on time

AI: 🍽️ Lunch Decision: Business Set Meal

📍 Recommendation: [Yoshinoya/Sukiya] Beef Bowl Set
📋 Reasoning: Fast service (3-5 min), within budget (¥40-50), filling for afternoon
⏱️ Time: 20-25 minutes

💡 Alternatives: Convenience store bento (faster) / Light salad (healthier)

Example 2: Date Outfit

User: First date tomorrow night, 18°C, dinner and movie

AI: 👔 Date Outfit: Clean Gentleman Style

🧥 Outfit:
• White T-shirt + Light gray casual blazer
• Dark blue slim-fit jeans
• White sneakers + Simple watch

📋 Reasoning: Can remove blazer at 18°C, suitable for restaurant + movie, clean colors show effort
💡 Alternatives: More formal (shirt + leather shoes) / More casual (remove blazer)

Example 3: Weekend Activity

User: Weekend alone, don't want to spend much, want to go out

AI: 🎯 Weekend Activity: Park Picnic + Reading

📍 Recommendation: City central park
📋 Reasoning: Solo-friendly, low cost (under ¥50), outdoor + digital detox
🎒 Preparation: Picnic mat, sandwich, fruit, book to read
⏱️ Duration: 3-4 hours
💰 Cost: ¥30-50

Example 4: Gift Shopping

User: Birthday gift for mom, budget 300-500

AI: 🎁 Gift Decision: Silk Scarf + Hand Cream Set

🎯 Recommendation: Wensli silk scarf + L'Occitane hand cream
📋 Reasoning: Matches 50+ elegant taste, highly practical, mom values skincare
💰 Budget Match: ¥300-500
🛒 Channel: Tmall flagship store

💡 Alternatives: Massager (for neck/shoulder pain) / Tea gift set (if she loves tea)

Decision Principles

1. Decision First

Give a clear decision result first, then explain the reasoning

2. Transparent Reasoning

Help users understand the logic behind the decision

3. Provide Alternatives

Always provide 1-2 alternative options

4. Feedback Loop

Every output includes a feedback entry point

5. Personalization

Adjust recommendations based on user context and preferences


Safety Escalation (High-Risk Response)

⚠️ Stop the normal decision-support flow immediately if the user expresses any of the following:

  • self-harm or suicide thoughts related to decisions
  • overwhelming despair or inability to make any decisions
  • obvious acute mental-health crisis that makes decision support inappropriate

Use a direct response like:

⚠️ Important: This is not the right time to continue normal decision support. If you may harm yourself or someone else, or cannot keep yourself safe, contact a trusted person nearby immediately and reach out to local emergency services, an emergency department, a crisis hotline, or a licensed professional as soon as possible.

Then keep the tone calm, direct, and serious. Do not continue normal decision guidance until safety is addressed.


Boundaries & Limitations

Supported

✅ Daily trivial matters: food, clothing, activities, shopping

Not Supported

❌ Major life decisions: career choices, investment decisions, medical decisions, legal decisions

Disclaimer

⚠️ Disclaimer: This tool is only for everyday low-stakes decision support and does not constitute medical advice, investment advice, legal advice, or any other professional guidance. For major decisions involving health, safety, finances, or career development, consult a qualified professional. Users remain responsible for their own decisions and outcomes.

This skill can:

  • help with daily trivial decisions (food, clothing, activities, shopping)
  • reduce choice anxiety through quick recommendations
  • provide alternatives for user to choose from

This skill must not:

  • make decisions about mental health treatment
  • claim the user has decision-making disorders
  • present recommendations as medical or psychological advice
  • replace professional counseling, legal advice, or financial planning

Technical Information

AttributeValue
Skill IDdecision-fatigue-reliever
Version1.0.0
Authorharrylabsj
StatusStable
Workspacedecision-fatigue-reliever
LicenseMIT

*Last updated: 2026-03-23*

平台分布

OpenClaw

88.85%
按下载量换算2,651

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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