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Agent Skill · 效率

game-design-fogg-behavior-audit(游戏设计 fogg 行为审核)

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

game-design-fogg-behavior-audit 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 17,610。

总安装 2,546周安装 104GitHub Stars 公开资料未说明下载 824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
1.0.0

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:game-design-fogg-behavior-audit(游戏设计 fogg 行为审核)
来源仓库:https://github.com/stanestane/game-design-fogg-behavior-audit
安装命令:
openclaw skills install game-design-fogg-behavior-audit
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 game-design-fogg-behavior-audit

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。

game-design-fogg-behavior-audit 依据行为模型拆解操作步骤实现动机驱动。识别阻碍转化的摩擦点并设计 nudging 干预策略。广泛应用于新手引导、付费转化等关键行为漏斗优化。无需联网即可本地运行,保护敏感业务逻辑不外泄。必须明确定义目标行为与当前障碍才能有效开展工作。

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 game-design-fogg-behavior-audit;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

game-design-fogg-behavior-audit 怎么安装?

在终端执行 openclaw skills install game-design-fogg-behavior-audit。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

game-design-fogg-behavior-audit 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。

game-design-fogg-behavior-audit 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。

game-design-fogg-behavior-audit 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。

game-design-fogg-behavior-audit 用的人多吗?

公开数据是累计安装 2,546 次,近一周安装 104 次,下载 824 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。

game-design-fogg-behavior-audit 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
game-design-fogg-behavior-audit

游戏设计 fogg 行为审核 · 本页

2,546—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
game-design-fogg-behavior-audit
description
Audit a game feature, flow, event, onboarding step, progression action, monetization surface, retention mechanic, or social prompt using the Fogg Behavior Model: Motivation, Ability, Prompt. Use when evaluating whether a design actually causes the intended player behavior, diagnosing weak feature adoption, identifying friction or mistimed prompts, or understanding why a feature that seems valuable is not being used.

Game Design Fogg Behavior Audit

Evaluate whether a feature actually produces the behavior it is trying to cause.

Use this skill when the main question is behavioral: will players do the thing, and if not, why not? The goal is not to give a broad aesthetic critique. The goal is to identify whether the intended player action is supported by enough motivation, enough ability, and the right prompt at the right moment.

Read references/fogg-notes.md when you need a concise reminder of the model and the main failure patterns. Read references/game-examples.md when you want examples of how Motivation, Ability, and Prompt show up in game features.

Core behavior

  • Keep the analysis practical, not academic.
  • Always identify the target behavior first.
  • Do not audit a feature in the abstract if the intended player action is unclear.
  • Evaluate Motivation, Ability, and Prompt separately before giving a verdict.
  • Identify which of the three is the main bottleneck.
  • Recommend specific fixes, not vague advice.
  • Focus especially on feature design, onboarding, retention loops, event participation, progression actions, social actions, and monetization prompts.

What to ask first

Prioritize these questions:

  1. What exact player behavior is this feature trying to cause?
  2. What is the feature or flow?
  3. Who is the target player or player state?
  4. When is the player supposed to do the action?
  5. What reward, value, urgency, or reason does the player have to do it?
  6. What friction, prerequisites, or UI steps stand between the player and the action?
  7. What prompt or trigger is currently used?

If the target behavior is vague, ask for clarification or infer the most likely behavior and state the assumption.

What to diagnose

Quickly identify:

  • whether the intended behavior is clear and specific
  • whether players have enough reason to do it now
  • whether the action is easy enough in the current context
  • whether the prompt appears at the right moment
  • whether the prompt is visible, timely, and relevant
  • whether the feature is failing mostly because of low motivation, low ability, weak prompting, or a mismatch between all three

Response structure

Always organize the answer using this structure.

Target Behavior

  • state the exact player action the feature is trying to produce
  • if needed, distinguish primary and secondary behaviors

Motivation Read

  • what makes the player want to do it
  • what weakens desire or relevance
  • whether the reward, emotional appeal, status, urgency, curiosity, fear of loss, or identity fit is strong enough

Ability Read

  • what makes the action easy or hard
  • clarity
  • step count
  • cognitive load
  • time cost
  • resource or skill gates
  • UI friction

Prompt Read

  • what currently prompts the behavior
  • whether the prompt is visible, understandable, and well-timed
  • whether the prompt hits when motivation and ability are high enough

Failure Diagnosis

  • identify the main bottleneck
  • say whether the feature mostly fails because players do not want it, cannot easily do it, are not being prompted well, or are being prompted at the wrong time

Recommendation

  • recommend specific changes
  • if useful, separate fixes into motivation, ability, and prompt improvements

Strong use cases

This skill is especially useful for:

  • FTUE and tutorial steps
  • daily or return-player actions
  • event entry and event participation
  • reward claims and progression interactions
  • store offers and monetization prompts
  • battle pass or mission adoption
  • social invites or guild actions
  • underused buttons, tabs, or feature entries
  • any feature that seems valuable on paper but is not being used much

Weaker use cases

This skill is less useful for:

  • broad game vision critique without a specific target behavior
  • purely aesthetic review
  • open-ended sandbox play where the intended behavior is intentionally loose
  • high-level worldbuilding analysis

Style guidance

  • Be concrete.
  • Do not turn the analysis into generic behavioral-science fluff.
  • Keep the focus on what the player is actually being asked to do.
  • If the feature is trying to drive too many behaviors at once, say so.
  • If the behavior target itself is bad or confused, say that before tuning Motivation, Ability, or Prompt.

Fast mode

Use this compressed flow when the user wants a quick answer:

  • what exact behavior is this feature trying to cause
  • do players want to do it
  • can they easily do it
  • are they prompted at the right moment
  • which of the three is weakest
  • what should change first

Working principle

A feature does not succeed just because it exists, is visible, or is theoretically valuable. It succeeds when the player has enough reason to act, enough ability to act, and a prompt that lands at the right moment.

平台分布

OpenClaw

93.06%
按下载量换算767

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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