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dogfoodingdogfooding 演示文稿

Agent Skill

dogfooding 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

总安装

24,423

周安装

988

GitHub Stars

734

下载量

7,667
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:dogfooding(dogfooding 演示文稿)
来源仓库:https://github.com/refoundai/lenny-skills
仓库路径:skills/dogfooding
安装命令:
npx skills add https://github.com/refoundai/lenny-skills --skill dogfooding
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/refoundai/lenny-skills --skill dogfooding

简介

帮助团队建立强烈的内部产品使用文化,以发现真正的用户痛点。

  • 专注于两个核心实践:要求所有团队成员成为自己产品的活跃用户,并每天大量使用该产品进行实际工作而不是演示测试
  • 提供一个四步实施框架:评估当前的使用水平,确定第一手经验中的差距,设计使内部测试自然且必要的系统,并衡量对产品决策的影响
  • 标记五个常见错误,包括肤浅的测试、委托给 QA 而不是要求团队范围内使用,以及忽略超出快乐路径的边缘情况
  • 包括诊断问题,帮助团队了解采用障碍并将测试见解与产品改进联系起来

SKILL.md

Dogfooding

Help the user implement effective dogfooding practices using frameworks from 2 product leaders who have built cultures of intense internal product usage.

How to Help

When the user asks for help with dogfooding:

  1. Assess current state - Determine how much the team currently uses their own product
  2. Identify the gap - Find where team members lack firsthand experience with user pain points
  3. Design the program - Help create systems that make dogfooding natural and required
  4. Measure impact - Track how dogfooding improves product decisions

Core Principles

Require team members to become users

Maya Prohovnik: "I am constantly yelling at my product team who do not have podcasts and being like, I really don't think that you can build the right things. If they talk to users all the time, they see the data, but all of them, once they finally start doing their podcast, they're like, I get it." Force the entire team to become creators/users to deeply understand user pain points.

Use the tool intensely every day

Michael Truell: "From the very start, our product development process was really about dogfooding, and using the tool intensely every day. And we never wanted to ship anything that wasn't useful to us." 'Intense' daily use provides the realism needed to build useful features, especially for AI products.

Questions to Help Users

  • "How often does each team member actually use the product as a real user?"
  • "What's preventing your team from being heavy users of your own product?"
  • "What would it take to make internal usage feel natural rather than forced?"
  • "Are you learning different things from dogfooding vs. customer feedback?"
  • "How quickly do you feel the pain of bugs or friction when using your own product?"

Common Mistakes to Flag

  • Superficial testing - Using the product only in demo mode, not for real work
  • Delegating to QA - Relying on testers instead of requiring team members to be real users
  • Ignoring non-obvious use cases - Only testing the happy path rather than edge cases
  • Not acting on findings - Dogfooding without a process to fix discovered issues
  • Excluding non-product roles - Only having engineers dogfood when designers and PMs should too

Deep Dive

For all 2 insights from 2 guests, see references/guest-insights.md

Related Skills

  • Writing North Star Metrics
  • Defining Product Vision
  • Prioritizing Roadmap
  • Setting OKRs & Goals

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

39.32%
按下载量换算3,015

Claude

29.64%
按下载量换算2,272

Cursor

18.19%
按下载量换算1,395

Gemini CLI

9.93%
按下载量换算761

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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