ai-assist-dockerize-website
Guide the user through containerizing and serving a simple website or documentation folder with Docker — inspects the project to detect what to serve (ready-to-serve static HTML, a buildable site that emits static output, or a raw markdown/docs folder that needs rendering), gener
供给资产档案
研究与知识工作
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
场景
研究 Agent
I need my agent to research a topic, compare sources, and produce a concise report.
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 jparkerweb/ai-assist-skills --skill ai-assist-dockerize-website
维护状态
新鲜
今天有推送
风险
需审查
许可证不清晰
GitHub 质量
88
61/100 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
88 个 GitHub Stars
仓库活跃度
88 个 Star,12 个 Fork
维护状态
今天有推送
许可证
未知
安装
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-dockerize-website
安装安全性
标准软件包或运行时安装路径
权限范围
secrets or environment access, shell or command execution
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 creates ambiguity about the legal terms for reuse.
- Financial research output is not financial advice; require human review before any live investment decision.
- 许可证不清晰
- Quality score needs review
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
- 研究 Agent 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
- 检索来源
适用 Agent
安装决策
- 命令
- npx skills add jparkerweb/ai-assist-skills --skill ai-assist-dockerize-website
- 策略
- 阻止
- 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
安装命令
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-dockerize-website不适用场景
- 需要厂商支持 SLA 的团队
- production agents without a repository review
- Repository license is unknown, which creates ambiguity about the legal terms for reuse.
- 高风险权限提示:Shell or command execution, Secrets or environment access
- 许可证不清晰
替代 Skill
Last30days Skill
53.5K Stars
npx skills add mvanhorn/last30days-skill -g
替代 Skill
Academic Research Skills
38.4K Stars
npx skills add Imbad0202/academic-research-skills
替代 Skill
GPT Researcher
28.0K Stars
npx skills add assafelovic/gpt-researcher
替代 Skill
DeepResearch
19.8K Stars
npx skills add Alibaba-NLP/DeepResearch
Agent 安全 v2
26/100 · 避免自动安装
This skill should not be selected by an agent without explicit human security review.
Do not auto-install. Inspect the source, dependencies, and permission surface first.
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 or command execution, Secrets or environment access
- 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 jparkerweb-ai-assist-dockerize-websiteAgent 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%20ai-assist-dockerize-website%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve 文本
/api/agent/resolve?task=Use%20ai-assist-dockerize-website%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
安装交接
/api/skills/jparkerweb-ai-assist-dockerize-website/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 ai-assist-dockerize-website in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20ai-assist-dockerize-website%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-dockerize-website/install
Install command: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-dockerize-website
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/jparkerweb-ai-assist-dockerize-website/install
LLM 文本格式
/api/skills/jparkerweb-ai-assist-dockerize-website/install?format=text
寻找替代方案
/api/skills/search?q=ai-assist-dockerize-website&limit=3
Agent 提示词
Use ai-assist-dockerize-website for this task. Review https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-dockerize-website/install, then install with: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-dockerize-websiteRegistry 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/jparkerweb-ai-assist-dockerize-website
LLM 文本
/api/registry/manifest/jparkerweb-ai-assist-dockerize-website?format=text
安装别名
/api/registry/install/jparkerweb-ai-assist-dockerize-website
推荐
/api/registry/recommend?task=Use%20ai-assist-dockerize-website%20in%20an%20agent%20workflow&limit=3
Agent 决策面板
Fallback candidate for Research agents
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
研究 Agent
信任标签
先做原型验证
安装路径
命令已就绪
适用场景
- 研究 Agent 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
- 61/100 质量档案
- 10 个 OpenAgentSkill 交互事件
先审查
- Repository license is unknown, which creates ambiguity about the legal terms for reuse.
实施路径
- 1在沙盒 Agent 中安装它,并端到端完成一次研究 Agent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88 个 GitHub Stars
Star/Fork 活跃度
检查88 个 Star,12 个 Fork; 当前元数据中没有议题活跃度信息
近期维护
通过今天有推送
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 creates ambiguity about the legal terms for reuse.
- Financial research output is not financial advice; require human review before any live investment decision.
- 许可证不清晰
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 88 GitHub stars
- Stars/forks activity: 88 stars, 12 forks; issue activity unavailable in current metadata
- License clarity: Unknown
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- 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
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Operate local tools
Local desktop
I need my agent to operate local files and desktop apps in a repeatable workflow.
Operate web apps
Browser automation
I need my agent to control a browser, fill forms, and verify web app workflows.
工作流匹配
加入完整工作流
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
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.
Scrape, clean, and reuse web data
Web data pipeline
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
替代方案短名单
安装前对比
可能适合该任务的相近 Skill。
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GPT Researcher
Run autonomous deep research over web and local sources
DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
概览
--- name: ai-assist-dockerize-website description: "Guide the user through containerizing and serving a simple website or documentation folder with Docker — inspects the project to detect what to serve (ready-to-serve static HTML, a buildable site that emits static output, or a raw markdown/docs folder that needs rendering), generates a Dockerfile, .dockerignore, docker-compose.yml, helper run/build commands, and a 'Running with Docker' README section, then offers to build and smoke-test the container and publish the image to Docker Hub or GHCR. Uses nginx:alpine for static content and a multi-stage build when the site must be generated. Only invoke when the user explicitly types /ai-assist-dockerize-website. Never auto-trigger from general conversation about Docker, containers, websites, or Dockerfiles." argument-hint: "[path-to-site-or-docs-folder] [--port <port>]" ---
# Dockerize a Website
This skill is invoked **manually** — only when the user explicitly runs `/ai-assist-dockerize-website`. Don't auto-trigger it from general talk about Docker, containers, or websites.
Guide the user from a project folder to a working Docker container that serves their site or documentation. The skill is **interactive and guided**, not a one-shot script: inspect the project, propose a sensible plan, confirm a few details, generate the files, then offer to build/test and publish.
The spine is: **detect → confirm → generate → offer to test → offer to publish.** Lead with a good default at every step so the user is confirming, not configuring from scratch.
## When to use
Use this whenever the user wants to serve a *static* website or a *documentation* folder out of a container — loose HTML/CSS/JS, the build output of a site generator, or a folder of markdown docs. The "project with a docs folder" case is the bullseye.
## Out of scope — dynamic apps
This skill serves static content. If the project is a **dynamic app** that runs code per request — an Express/Fastify/Nest server, Next.js in SSR mode, Flask/Django/FastAPI, a Go/Rust web server, anything with a long-running `start`/`serve` process and a port it listens on — stop and say so plainly. Containerizing those means basing the image on the app's own runtime and running its start command, which is a different job. Detect this case (see below), tell the user, and don't half-build a static image that won't actually run their app.
Don't leave them stranded, though. After declining, offer a real next step: a correct container for a dynamic app is based on the app's own runtime (e.g. `node:22-alpine`), installs its dependencies, runs the start command, and exposes the port the app listens on. Offer to hand-write that separately — it's just outside this skill's static-hosting scope.
## Step 1 — Inspect and classify the project
Before asking anything, look at what's there so the proposal is concrete. If the user named a folder (argument or in their message), focus on it; otherwise scan the working directory.
Classify into one of four strategies:
| Signals found | Strategy | |---|---| | An `index.html` ready to serve — at the project root, or in `dist/`, `build/`, `out/`, `public/`, `_site/`, `site/`, `www/` | **A · Ready static** — single-stage nginx, copy the folder in | | Site-generator tooling: `package.json` with a `build` script + a static framework (Vite, Astro, Eleventy, Docusaurus, Gatsby, SvelteKit static), or a config file (`mkdocs.yml`, `docusaurus.config.*`, `astro.config.*`, `_config.yml`, `hugo.toml`/`config.toml`, `.eleventy.js`) | **B · Buildable** — multi-stage build → nginx | | A folder of `.md` docs with **no** generator configured | **C · Raw docs** — offer to render (recommended) or serve as-is | | A long-running server: `package.json` `start` runs a server (`node server.js`), source calls `.listen()`, or a web framework (Express, Next SSR, Flask, Django, FastAPI, Go/Rust server) | **D · Dynamic app** — stop, explain, don't build |
State your finding in one line — e.g. *"Found a built site in `dist/` with an `index.html`, so I'll serve it directly with nginx (strategy A)."* — and let the user correct you if the detection is off.
For **strategy B and C**, the build/render details live in `references/recipes.md`. Read that file when you land on those paths — it has the multi-stage Dockerfiles per generator (Node SSGs, MkDocs, Hugo, Jekyll), the SPA fallback config, the raw-markdown render path, caching headers, the non-root variant, and a Caddy alternative.
## Step 2 — Confirm the details
Pre-fill every answer from Step 1 so these are quick confirmations, not an interrogation:
- **What to serve** — the folder (strategy A) or the build output directory (strategy B/C). Show the path you detected. - **Port** — what host port to expose. Default `8080` (avoids clashing with anything already on `80`). Honor `--port` if given. - **Image / container name** — propose one lowercase-hyphenated name for both. Default to the **project folder** name, but prefer a more meaningful name when one is obvious — a `package.json` `name`, or a clear title in the README — e.g. favor `marketing-site` over a generic folder like `app` or `vite-app`. Always let the user override. - **Compose?** — yes by default (one-command up/down). Mention they can skip it. - For **strategy C**, confirm they want the docs *rendered* (recommended — browsers download raw `.md` instead of displaying it) versus served as raw files.
Skip questions whose answers are obvious or already given. The user invited a guided flow, not a form.
## Step 3 — Generate the artifacts
Generate all of these, tailored to the chosen strategy. Substitute the real folder, port, and names — don't leave placeholders in the files you write.
### Dockerfile (strategy A — ready static)
```dockerfile # syntax=docker/dockerfile:1 FROM nginx:1.27-alpine
# Copy the site into nginx's web root. COPY <SITE_DIR>/ /usr/share/nginx/html/
EXPOSE 80
# Fail the container's health check if nginx stops serving. # busybox wget ships in the alpine image, so no extra install is needed. HEALTHCHECK --interval=30s --timeout=3s --start-period=5s \ CMD wget -q --spider http://localhost/ || exit 1 ```
Pin the base image to a real minor tag (e.g. `nginx:1.27-alpine`) rather than the floating `nginx:alpine`, so a rebuild months from now doesn't silently pull a different nginx. Mention this so the user knows to bump it deliberately.
The build context is the project root (compose uses `build: .`), so `COPY` paths are relative to it: copy the served folder by its path from the root — `COPY public/ …` when the site lives in `public/`, or `COPY . …` when the site *is* the project root (then lean on `.dockerignore` to keep junk out).
For **strategy B/C**, use the matching multi-stage Dockerfile from `references/recipes.md` — a builder stage runs the generator, and only its static output is copied into the nginx stage, so build tooling never ships in the final image.
### .dockerignore
Keep the build context small and the image clean:
```gitignore .git .gitignore node_modules npm-debug.log* .env .env.* .DS_Store Thumbs.db Dockerfile* .dockerignore docker-compose*.yml ```
Tailor it to the project. For a multi-stage build (strategy B/C), also ignore the local build-output directory (`dist`, `build`, `_site`, `out`, `site`, …) — it's regenerated inside the image, and shipping a stale host copy into the build context only bloats it. The "don't ignore your content" rule is about *source* you serve directly (strategy A), not generated output.
### docker-compose.yml
```yaml services: web: build: . image: <IMAGE_NAME>:latest container_name: <CONTAINER_NAME> ports: - "<HOST_PORT>:80" restart: unless-stopped healthcheck: test: ["CMD", "wget", "-q", "--spider", "http://localhost/"] interval: 30s timeout: 3s retries: 3 start_period: 5s ```
No top-level `version:` key — it's obsolete in Compose v2 and prints a warning.
### Helper commands + README section
Append a "Running with Docker" section to the project's `README.md` (or create a short `DOCKER.md` if there's no README). The commands are identical in PowerShell and bash, so no per-shell variants are needed.
The block below is the template; its outer 4-backtick fence is only the boundary so the inner blocks display here. When you write the actual file, use normal **3-backtick** fences for the `bash` blocks — don't copy the 4-backtick wrapper.
````markdown ## Running with Docker
This site is served by nginx in a container.
### Quick start (Docker Compose)
```bash docker compose up -d --build # build the image and start in the background # open http://localhost:<HOST_PORT> docker compose logs -f # follow logs docker compose down # stop and remove ```
### Without Compose
```bash docker build -t <IMAGE_NAME> . docker run -d --name <CONTAINER_NAME> -p <HOST_PORT>:80 <IMAGE_NAME> docker stop <CONTAINER_NAME> && docker rm <CONTAINER_NAME> ``` ````
After writing the files, summarize what you created and the one command to run it.
## Step 4 — Offer to build and smoke-test
Don't build automatically — the user may not have Docker running, or may want to review the files first. Ask: *"Want me to build it and confirm it serves?"*
If yes:
1. Check the daemon is up first with `docker info`. If it fails, tell the user to start Docker Desktop and stop here — the files are already written and ready whenever they are. 2. Build and start: `docker compose up -d --build` (or `docker build` + `docker run` if they skipped compose). 3. Smoke-test the URL — request `http://localhost:<HOST_PORT>/` and confirm an HTTP 200 with non-empty HTML. On Windows use `curl.exe` or PowerShell's `Invoke-WebRequest`; give nginx a second to come up and retry once or twice before calling it a failure. 4. Report the result. Leave it running if they want to look at it, or tear down with `docker compose down`. If you started a throwaway container by hand, clean it up.
If the build or smoke-test fails, read the actual error (`docker compose logs`) and fix the real cause — a wrong output directory, a missing build step, a port already in use — rather than guessing.
## Step 5 — Offer to publish (optional)
Once it runs locally, offer to push the image to a registry so it can be shared or deployed. Only do this if the user wants it. Read `references/registry-publish.md` for the Docker Hub and GHCR walkthrough (login, tag, push, image naming, and the multi-arch `--platform` note for Apple-Silicon-built images headed to amd64 servers).
## Conventions and rationale
- **nginx:alpine for static** — tiny, battle-tested, zero app code to maintain. Reach for the Caddy alternative (in recipes) only when the user wants dead-simple config or automatic file serving. - **Multi-stage when building** — the final image carries only the rendered site, not Node/Python/Hugo and their caches. Smaller image, smaller attack surface. - **Pin the base image** to a minor tag so rebuilds are reproducible. - **Default to port 8080** on the host to avoid colliding with whatever already owns `80`. - **Non-root** is available via `nginxinc/nginx-unprivileged` (recipes) for stricter environments — note it as an option rather than forcing it. - **No secrets in the image** — static hosting rarely needs any; if the user mentions API keys or env config, that's a sign this is really a dynamic app (strategy D).
## Reference files
- `references/recipes.md` — multi-stage Dockerfiles per generator (Node SSGs, MkDocs, Hugo, Jekyll), the raw-markdown render path, SPA fallback, caching headers, non-root, and the Caddy alternative. Read it for strategy B or C. - `references/registry-publish.md` — pushing the image to Docker Hub or GHCR. Read it for Step 5.
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21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 ai-assist-dockerize-website 准备的场景化草稿,可手动发布到 X。
ai-assist-dockerize-website: Guide the user through containerizing and serving a simple website or documentation folder wi... 88 stars https://www.openagentskill.com/skills/jparkerweb-ai-assist-dockerize-website?ref=x
可选:带安装命令的回复
Listing + install path for ai-assist-dockerize-website: https://www.openagentskill.com/skills/jparkerweb-ai-assist-dockerize-website?ref=x Install: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-dockerize-website
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
- jparkerweb
- 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 jparkerweb,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/jparkerweb-ai-assist-dockerize-website)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-dockerize-website)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-dockerize-website/audit)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-dockerize-website)作者
jparkerweb
@jparkerweb
健康信号
- GitHub Stars
- 88
- 质量评分
- 37/100
- 最近 GitHub 推送
- 2026年8月22日
- 框架提示
- 未知
- OpenAgentSkill 浏览量
- 10
- 复制安装命令
- 0
- 跳转点击
- 0
社区信号
告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。
信任与安全
Do not auto-install
- GitHub 采用度88 个 GitHub Stars检查
- Star/Fork 活跃度88 个 Star,12 个 Fork; 当前元数据中没有议题活跃度信息检查
- 近期维护今天有推送通过
- 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, credential or environment access修复
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