epic-workshop
Use when generating, planning, authoring, or recording an Epic Web / Epic React style workshop, exercise, tip, or video. Applies Kent C. Dodds' "How to be an Epic Instructor" principles to workshop design, exercise structure, recording, and material delivery, and encodes Epic Web
供给资产档案
编程与开发 Agent
代码审查、仓库分析、测试、CI、GitHub、DevOps 与开发工作流 Skill。
场景
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
适配 Agent
Claude Code + Browser agents + CLI
适用于 Codex、Claude Code、Cursor、CLI 或自定义 Agent。
安装
就绪
npx skills add AlemTuzlak/skills --skill epic-workshop
维护状态
新鲜
距上次推送 3 天
风险
需审查
许可证不清晰
GitHub 质量
39
57/100 质量 · 62/100 信任
覆盖标签
审查说明
许可证不清晰 · Dependency or permission surface needs review
Agent 采用评分卡
一眼查看信任、审计与安装准备度
这些分数综合公开仓库元数据、OpenAgentSkill 审查信号、维护新鲜度与安装准备度。它用于候选筛选,不替代人工审查。
质量
有潜力有用的候选项,但采用前应与替代方案比较。
信任
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
审计
需审查对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。
OpenAgentSkill 信任评分 v5
安装前需人工审查
Choose a stronger alternative or inspect the source manually before any install attempt.
Stars
39 个 GitHub Stars
仓库活跃度
39 个 Star,0 个 Fork
维护状态
距上次推送 3 天
许可证
未知
安装
npx skills add AlemTuzlak/skills --skill epic-workshop
安装安全性
标准软件包或运行时安装路径
权限范围
shell or command execution, filesystem or document access
Agent 结果
暂未有 Agent 结果数据
文档
README/SKILL.md 上下文充分
风险摘要
生产前审查
- Repository license is unknown, which may complicate reuse and attribution.
- Financial research output is not financial advice; require human review before any live investment decision.
- 许可证不清晰
- Low GitHub adoption signal
安装准备度
安装路径可用
- 安装路径可用
- 仓库证据可用
- 许可证不清晰
- 暂无 Agent 验证结果证据
Agent 可读元数据
这个 Skill 的机器可读决策数据。
使用此区块或内嵌 JSON 判断 Agent 是否应安装该 Skill、选择替代方案,或先请求人工审查。
适用任务
- GitHub automation 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
- Inspect repository metadata
适用 Agent
安装决策
- 命令
- npx skills add AlemTuzlak/skills --skill epic-workshop
- 策略
- 审查
- 人工审查
- 是
信任与风险
- 信任
- 54/100
- 审计
- 70/100
- 风险级别
- 需审查
结果闭环
- 端点
- /api/agent/outcome
- 事件 ID
- resolve
- 结果
- 5
不适用场景
- 需要厂商支持 SLA 的团队
- production agents without a repository review
- Low GitHub adoption signal
- Repository license is unknown, which may complicate reuse and attribution.
- 高风险权限提示:Shell 或命令执行
替代 Skill
Frontend Design
171.1K Stars
npx skills add anthropics/skills --skill frontend-design
替代 Skill
Taste Skill: Anti-Slop Frontend
79.4K Stars
npx skills add Leonxlnx/taste-skill --skill design-taste-frontend
替代 Skill
Canvas Design
171.1K Stars
npx skills add anthropics/skills --skill canvas-design
替代 Skill
Anthropic Brand Guidelines
171.1K Stars
npx skills add anthropics/skills --skill brand-guidelines
Agent 安全 v2
34/100 · 避免自动安装
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
高
Shell 或命令执行
Skill 元数据引用了终端、CLI、Shell、子进程或命令执行工作流。
中
Browser automation
Skill may drive a browser or interact with web pages.
中
网络访问
Skill 可能访问远程页面、API、仓库或外部服务。
中
文件系统访问
Skill 可能读取或写入项目文件、文档、生成产物或本地工作区状态。
- 高风险权限提示:Shell 或命令执行
- 许可证不清晰
安装目标
在你的 Agent 工作流中安装此 Skill
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install alemtuzlak-epic-workshopAgent 解析计划
让 Agent 在安装前验证匹配度。
Resolve API 返回首选 Skill、替代方案、安全策略、审计说明、安装目标和可直接执行的提示词,无需抓取此页面。
打开 JSON
/api/agent/resolve?task=Use%20epic-workshop%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve 文本
/api/agent/resolve?task=Use%20epic-workshop%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
安装交接
/api/skills/alemtuzlak-epic-workshop/install
Agent 应检查
- 从 Resolve API 检查任务匹配与替代方案。
- 检查审计评分、信任评分和安全策略警告。
- 检查 Codex、Claude Code、Cursor 或 CLI 的安装目标兼容性。
复制提示词
Task: Use epic-workshop in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20epic-workshop%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/alemtuzlak-epic-workshop/install
Install command: npx skills add AlemTuzlak/skills --skill epic-workshop
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent 交接
把安装路径交给 Agent,而不是再给一个目录页。
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
安装交接
/api/skills/alemtuzlak-epic-workshop/install
LLM 文本格式
/api/skills/alemtuzlak-epic-workshop/install?format=text
寻找替代方案
/api/skills/search?q=epic-workshop&limit=3
Agent 提示词
Use epic-workshop for this task. Review https://www.openagentskill.com/api/skills/alemtuzlak-epic-workshop/install, then install with: npx skills add AlemTuzlak/skills --skill epic-workshopRegistry 元数据
用于自动选择 Skill 的 Agent 可读档案。
本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号,让 Agent 无需抓取界面即可排序。
Manifest
/api/registry/manifest/alemtuzlak-epic-workshop
LLM 文本
/api/registry/manifest/alemtuzlak-epic-workshop?format=text
安装别名
/api/registry/install/alemtuzlak-epic-workshop
推荐
/api/registry/recommend?task=Use%20epic-workshop%20in%20an%20agent%20workflow&limit=3
适配 Agent
GitHub automation
平台
Claude Code, Browser agents
Agent 决策面板
Fallback candidate for GitHub automation
先用此 Skill 做原型验证,并保留备选方案。
栈中角色
备选候选
主要匹配
GitHub automation
信任标签
先做原型验证
安装路径
命令已就绪
适用场景
- GitHub automation 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
证据
- 仓库近期活跃
- 已提供安装命令或 GitHub 仓库
- 57/100 质量档案
- 4 个 OpenAgentSkill 交互事件
先审查
- Low GitHub adoption signal
- Repository license is unknown, which may complicate reuse and attribution.
实施路径
- 1在沙盒 Agent 中安装它,并端到端完成一次GitHub automation任务。
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
信任档案
Do not auto-install
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
GitHub 采用度
检查39 个 GitHub Stars
Star/Fork 活跃度
检查39 个 Star,0 个 Fork; 当前元数据中没有议题活跃度信息
近期维护
通过距上次推送 3 天
许可证清晰度
检查未知
积极信号
- AI 审查已通过
- 安装路径可用
- 仓库证据可用
- 近期维护的仓库
- 安装命令未发现明显高风险模式
- 结果闭环已就绪,但需要首次真实 Agent 运行
安装前审查
- Repository license is unknown, which may complicate reuse and attribution.
- Financial research output is not financial advice; require human review before any live investment decision.
- 许可证不清晰
- Low GitHub adoption signal
- Quality score needs review
- Permission surface needs review: shell or command execution, filesystem or document access
- GitHub adoption: 39 GitHub stars
- Stars/forks activity: 39 stars, 0 forks; issue activity unavailable in current metadata
- License clarity: Unknown
- Dependency/runtime risk: command execution surface, network or browser surface
- 暂未有真实 Agent 结果报告
- 无人值守安装前需要人工审查
建议操作
Choose a stronger alternative or inspect the source manually before any install attempt.
质量档案
有潜力 适用于 Agent 工作流的候选
有用的候选项,但采用前应与替代方案比较。
工作流匹配
在这些场景使用此 Skill
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Operate web apps
Browser automation
I need my agent to control a browser, fill forms, and verify web app workflows.
Operate local tools
Local desktop
I need my agent to operate local files and desktop apps in a repeatable workflow.
工作流匹配
加入完整工作流
Operate and verify web apps
Browser QA agent
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Design, build, test, and ship interfaces
Frontend and UI
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Inspect, patch, and verify code
Coding review agent
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
替代方案短名单
安装前对比
可能适合该任务的相近 Skill。
Frontend Design
Guidance for distinctive, intentional UI design, typography, visual direction, and non-template-like product interfaces.
Taste Skill: Anti-Slop Frontend
Design and implementation guidance for distinctive landing pages, portfolios, product demos, and purposeful redesigns.
Canvas Design
Create original visual art, posters, PNG assets, and PDF documents through a clear design philosophy.
Anthropic Brand Guidelines
Apply Anthropic official brand colors, typography, and visual standards to appropriate Anthropic-related artifacts.
概览
--- name: epic-workshop description: Use when generating, planning, authoring, or recording an Epic Web / Epic React style workshop, exercise, tip, or video. Applies Kent C. Dodds' "How to be an Epic Instructor" principles to workshop design, exercise structure, recording, and material delivery, and encodes Epic Web's exercise-comment emoji conventions. Used to generate workshops following https://www.epicweb.dev/get-started. Triggers on "create a workshop", "generate a workshop", "design an exercise", "record a workshop video", "Epic workshop", "Epic Web", "Epic React", or `/epic-workshop`. ---
# Epic Workshop
Generates and shapes Epic Web / Epic React style workshops. Encodes Kent C. Dodds' "How to be an Epic Instructor" guidance plus Epic Web's exercise-comment emoji conventions. Use whenever the user is producing teaching material in the Epic Web style — workshops, exercises, tips, recorded videos, or workshop apps.
The end goal is a workshop that fits the Epic Web getting-started flow at https://www.epicweb.dev/get-started — meaning it runs in the Epic workshop app (kcdshop), follows the welcome → exercise (intro → problem → solution → outro) → outro structure, and uses the emoji-key conventions in exercise comments.
## When this skill applies
Invoke when the user is doing any of:
- Designing a new workshop (topics, exercises, sequencing) - Writing exercise problem/solution material - Planning workshop video recordings - Setting up the workshop app for a new workshop - Reviewing existing workshop material against Epic standards - Scheduling, pricing, or running a live workshop - Recording tips or supplementary content tied to a workshop
## Guiding principles (these override generic instructional-design advice)
### 1. Opinions and consistency
The product is **the instructor's opinion**, not a survey of options. Learners are paying to skip analysis paralysis. So:
- Pick one solution and teach it deeply. Don't teach Next.js + Remix + Astro side-by-side. - **Heuristic:** if it would not make sense to use both tools/approaches in the same app, teach only one. If both would coexist in a real app (e.g. in-memory cache + SQLite cache), teach both. - Avoid contradicting earlier material or other Epic instructors. Consistency across the curriculum matters.
When the user proposes covering "multiple approaches," challenge it against this heuristic before agreeing.
### 2. Avoid distraction
Match example complexity to the format:
- **Tip / standalone video** → can use a richer, more domain-specific context (full app) - **Workshop exercise** → must use a simple, isolated example, OR a domain the learner has been progressively built up to in earlier exercises - **Screen setup** → defer to [howtoegghead.io](https://howtoegghead.com/instructor/screencasting/) for screencast hygiene; minimize on-screen clutter - **Face on camera** → encouraged (small corner circle is fine, no green screen required); makes flow more natural and reduces editing
If an exercise requires the learner to "onboard" to the example before learning can start, the example is too domain-specific.
### 3. Problems before solutions
Never present a solution without first establishing the problem. The pattern:
1. State the goal 2. Try the obvious-but-wrong approach (or a couple of them) 3. Show why it fails 4. Then introduce the real solution
Reference example: Simon's Tailwind glassmorphism tip — `bg-transparent` → fail → `bg-white/20` → `blur-md` → fail → real solution.
Cap this at 1–2 wrong attempts. Don't enumerate every possible misstep.
### 4. Desirable difficulties
Workshops follow **problem → learner attempts → solution**, not "watch me code." The learner's failure during the attempt is the learning event. When designing exercises:
- The problem step must be solvable enough that a motivated learner can make progress, but hard enough that they engage - The solution step reveals the canonical answer after they've tried - Don't collapse problem + solution into a single "follow along" video - **Don't spoil the limitation a later step resolves.** When a section is a staged arc — each step's pain motivates the next — the section/exercise *intro* and problem framing must not pre-announce those limitations (e.g. "wait 20–30s for one card", "each new question replaces the previous one"). Naming the gotcha upfront steals the discovery: the learner skims past the slow render or the vanishing card because they were told to expect it, instead of *feeling* it and wanting the fix. Describe what each step builds, not the wall it exposes — then let them hit the wall and make the next step the relief. (Foreshadowing the limitation is fine *after* the learner has experienced it — that's what the solution outro and 👨💼 Peter are for.)
### 5. Experience-based instruction
Don't teach a tech you've only spent two hours with. Either:
- Ship something real with it, or - Spend serious time using it and talking to people who have shipped with it
Workshops iterate through live delivery. The rule: **never give the same workshop twice without changes**. Take notes on every live delivery — split exercises, delete exercises, add exercises, even split a workshop into multiple workshops. Only record after several live deliveries have stabilized the material.
### 6. Instructors make their own demos
The instructor authors the exercise material themselves. Outside help is fine for design polish or feedback, but the instructor owns the demo end-to-end. This is non-negotiable for live Q&A quality.
### 7. Give freely
- All workshop material is open source on GitHub - Free articles, tips, talks, tutorials are *encouraged* alongside paid material — they don't cannibalize, they amplify - Long instruction blocks often graduate into standalone blog posts; tangents become tips. Both can be linked back from exercise instructions.
## Workshop structure
Every workshop has these video categories (mirror this structure when planning):
- Workshop welcome - Exercise intro - Exercise step: **Problem** - Exercise step: **Solution** - Exercise outro - Workshop outro
Reference: https://foundations.epicweb.dev/
Exercises are embedded in the workshop app (https://github.com/epicweb-dev/kcdshop). Videos published on epicweb.dev are embedded back into instructions via:
```html <EpicVideo url="https://www.epicweb.dev/workshops/.../solution" /> ```
## Solution step README (the step outro)
Each exercise step has a problem `README.mdx` (the instructions) and a solution `README.mdx`. **The solution README is not a technical changelog of the diff the learner just wrote — it's the emotional and narrative beat that closes the step.** The learner already did the work and can read their own code; this README lands the win and sets up the next step. Keep it short and warm, in this shape:
1. **One-sentence celebration of what they just shipped**, in plain excited language — not a bulleted recap of the implementation. e.g. *"We got the chat working server-side and now we're streaming messages — amazing!"* Resist re-explaining the code line by line. 2. **Encourage them.** Tell them they did a good job, and mean it. 3. **Tell them to take a short break and refresh** before the next step. 4. **🧝♀️ Kellie the Co-worker (when applicable)** — what she's doing ahead of the next step. When the next exercise *starts from meaningfully different code than this solution left off* — because you (the instructor) changed things between steps so the learner can focus on the new concept — attribute that work to Kellie: *"🧝♀️ Kellie wired up X, Y, and Z for you so you can focus on [the new thing]."* This is what explains an otherwise-confusing jump in the starting code. If there's no significant instructor-made setup before the next step, leave Kellie out. 5. **👨💼 Peter the Product Manager (when applicable)** — what he wants next. Peter shows up specifically when you **intentionally left the implementation lacking** as foreshadowing: he plays the PM who noticed the gap (the bot answers off-topic questions, the table takes 30s to appear, etc.) and asks the learner to fix it next. This motivates the next step from a real product/user need rather than "here's the next API." If the next step isn't motivated by an intentional gap, leave Peter out.
Rules:
- **Short.** The overview is one or two sentences; the whole README is a few short beats, not a wall of text. If you're re-explaining code the learner just wrote, cut it. - **Don't force the cast.** Use Kellie only when there's real instructor-made setup to attribute, and Peter only when the next step is motivated by an intentional gap. If neither applies, celebrate + encourage + break is a complete solution README. - **Save deep "why it works" analysis for the problem README or a short 📝/🦉 aside** — the solution outro is for momentum and encouragement, not a lecture.
The same celebrate → encourage → break → hand-off rhythm applies to exercise outros (`FINISHED.mdx`), scaled up to close the whole exercise rather than one step.
## Instructions live in the file, not the README
**The learner should never have to flip back to the README to know what to type.** Actionable, step-by-step instructions — what to add, what to change, a spec of fields to fill in, code to uncomment — belong as 🐨/💰 comments *in the file the learner is editing*, right where the change happens. Put the work where the work is.
The problem `README.mdx` carries what the in-file comments can't: the motivation (what we're building and why), conceptual background (🦉), how to verify it works, and where to look when stuck. It orients; it doesn't instruct keystroke by keystroke.
Smell test: if the README has a numbered "do X, then Y, then Z" list that mirrors the 🐨 comments already in the file, you've split the instructions across two places and forced a context-switch. Move the actionable detail into the file and let the README point at it ("open these files in order — Kody and Marty walk you through each change"). And when you'd otherwise make the learner transcribe a spec from the README (e.g. a list of field descriptions to write), pre-write it in the file as commented code 💰 they uncomment instead — uncommenting beats transcribing.
## Logistics defaults
- **Length:** 5–6 hours including breaks (longer drains learners) - **Price:** ~$300–350 per day - **Frequency:** instructor's choice - **Venue:** Gather.town by default; otherwise instructor specifies - **Team needs from instructor:** dates, times, venue details, copy/description - **Code of conduct:** https://kentcdodds.com/conduct (PG content — keep it shareable with a 6-year-old) - **AI assistants:** use them on camera; teaching learners to evaluate AI output is part of the job
## Recording rules
- **Never show the workshop app on camera.** It evolves and dates the video. Show the playground in the editor / browser / terminal instead. - Record only after the workshop has been delivered live multiple times. - Face-in-corner is recommended. - Editing: self-edit, or upload raw to Dropbox for Skill Recordings editors (cost deducted from first royalties). - Screencast technical guidance: https://howtoegghead.com/instructor/screencasting/
## Process when invoked
When the user says "I want to create a new workshop" (or similar), run this flow before any material is written:
1. **Clarify the workshop topic and target audience.** Confirm the *one* opinionated stack/approach being taught. Surface and resolve any "should we cover X or Y" questions using the same-app heuristic. 2. **Validate experience.** Has the user shipped with this tech, or spent serious time with it? If not, flag it and discuss how to close the gap before teaching. 3. **Outline the exercise progression.** Each exercise must build on the previous so by the time a domain-specific exercise appears, the learner is already onboarded. Draft the exercise list before any code. 4. **For each exercise, draf
技术详情
- 版本
- 1.0.0
- 许可证
- Unknown
- 最近更新
- 2026年8月23日
- 发布时间
- 2026年8月19日
决策摘要
备选候选
仓库近期活跃
Agent 验证证据
Agent 验证证据
来自解析、审查、安装和一次小范围运行后的结果报告。
- 成功率
- —
- 近期失败
- —
- 结果
- 0
- 输出质量
- —
- 失败
- 0
- 不相关
- 0
- 安装次数
- 0
- 风险拦截
- 0
- 需要配置
- 0
- 生产环境
- 0
暂时没有 Agent 结果数据。首次 Agent 执行可以通过 /api/agent/outcome 报告成功、需要设置、风险拦截、失败或不相关。
增长闭环
分享工具包
为 epic-workshop 准备的场景化草稿,可手动发布到 X。
epic-workshop: Use when generating, planning, authoring, or recording an Epic Web / Epic React style worksho... 39 stars https://www.openagentskill.com/skills/alemtuzlak-epic-workshop?ref=x
可选:带安装命令的回复
Listing + install path for epic-workshop: https://www.openagentskill.com/skills/alemtuzlak-epic-workshop?ref=x Install: npx skills add AlemTuzlak/skills --skill epic-workshop
收录来源
Registry 收录
此列表来自公开来源,维护者认领获批前不会标记为官方。
- 创作者
- AlemTuzlak
- 收录方
- OpenAgentSkill 社区索引
归属链接指向公开仓库或创作者主页。创作者可认领列表以更新所有权信号。
认领此 Skill所有者认领
认领此 Skill 页面
这条 Registry 收录 列表归属于 AlemTuzlak,但尚未标记为官方。认领后可增加已验证所有者信号,使后续发布、安装和审计更新更值得信赖。
创作者外链工具包
将证据徽章加入你的 README
在开发者评估仓库的位置展示规范页面、当前信任与审计信号,以及真实的 Agent 验证证据。
[](https://www.openagentskill.com/skills/alemtuzlak-epic-workshop)
[](https://www.openagentskill.com/skills/alemtuzlak-epic-workshop)
[](https://www.openagentskill.com/skills/alemtuzlak-epic-workshop/audit)
[](https://www.openagentskill.com/skills/alemtuzlak-epic-workshop)作者
AlemTuzlak
@alemtuzlak
健康信号
- GitHub Stars
- 39
- 质量评分
- 34/100
- 最近 GitHub 推送
- 2026年8月20日
- 框架提示
- 未知
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信任与安全
Do not auto-install
- GitHub 采用度39 个 GitHub Stars检查
- Star/Fork 活跃度39 个 Star,0 个 Fork; 当前元数据中没有议题活跃度信息检查
- 近期维护距上次推送 3 天通过
- 许可证清晰度未知检查
- README/SKILL.md 完整度元数据包含足够的用法与工作流上下文通过
- 依赖与运行时风险command execution surface, network or browser surface检查
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