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Agent Skill · 开发

deploy(部署)

用于辅助云资源、部署、容器、基础设施和运维自动化任务。它适合让 Agent 检查配置、整理部署步骤、分析资源状态、生成排障思路或辅助云服务接入。使用时需要明确目标环境、账号权限、区域和资源组,区分本地测试与生产操作;涉及删除资源、重启服务、修改网络或权限配置时,应先确认影响范围。

deploy 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为操作浏览器;许可证信息还不明确,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 19,805。

总安装 256周安装 11GitHub Stars 16下载 90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
unknown

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:deploy(部署)
来源仓库:https://github.com/pipecat-ai/skills
仓库路径:skills/deploy
安装命令:
npx skills add https://github.com/pipecat-ai/skills --skill deploy
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/pipecat-ai/skills --skill deploy

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

用于辅助云资源、容器和基础设施部署。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。适合检查配置、整理部署步骤或分析资源状态。使用时需明确目标环境、账号权限和资源组。涉及删除或修改网络配置时应先确认影响范围。

deploy 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/deploy

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/pipecat-ai/skills --skill deploy;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

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

deploy 怎么安装?

在终端执行 npx skills add https://github.com/pipecat-ai/skills --skill deploy。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

deploy 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

deploy 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

deploy 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

deploy 用的人多吗?

公开数据是累计安装 256 次,近一周安装 11 次,下载 90 次,GitHub 16 星。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。

deploy 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
deploy

部署 · 本页

25616操作浏览器未明确有提醒

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

Deploy an agent to Pipecat Cloud. This skill walks through the full deployment process interactively, confirming each step with the user.

Arguments

/deploy [--config <PATH>] [--env <PATH>]
  • --config (optional): Path to pcc-deploy.toml. Defaults to pcc-deploy.toml in the current directory.
  • --env (optional): Path to .env file for creating secrets. If not provided, the skill will look for a .env file in the same directory as the config file.

Examples:

  • /deploy
  • /deploy --config examples/mybot/pcc-deploy.toml
  • /deploy --config examples/mybot/pcc-deploy.toml --env examples/mybot/.env

Prerequisites

Before starting, verify these prerequisites and inform the user about any that are missing:

  1. Pipecat Cloud CLI: Check if pc is installed by running pc --version. If not installed, tell the user to install it with uv tool install pipecat-ai-cli and stop.
  2. Pipecat Cloud authentication: Check if pc cloud auth whoami succeeds. If not authenticated, run pc cloud auth login --headless as a background task, then read the output file to extract the URL and six-digit code. Share both with the user so they can authenticate in their browser. Wait for the background task to complete before proceeding.
  3. Configuration file: Read the pcc-deploy.toml file (from --config argument or current directory). If it doesn't exist, tell the user they need a pcc-deploy.toml and stop. Parse and display the configuration to the user (agent_name, image, secret_set, etc.).

If any prerequisite fails, stop and clearly explain what needs to be fixed. Do not proceed to the next steps.

Deployment Method

After prerequisites pass, ask the user how they want to deploy using AskUserQuestion:

  • Cloud Build (Recommended): Pipecat Cloud builds your Docker image from source. No local Docker required.
  • Self-managed image: Build and push your own Docker image from your machine, then deploy.

Important: Running Commands

All pc cloud commands must be run from the directory containing the pcc-deploy.toml file. Use cd <dir> && <command> to ensure the correct working directory.

Several pc cloud commands prompt for interactive confirmation which doesn't work in this environment. Use --force to skip confirmation prompts:

  • pc cloud deploy: Use --force (e.g., pc cloud deploy --force)
  • pc cloud docker build-push: Use --force (e.g., pc cloud docker build-push --force)
  • pc cloud secrets set: Use the --skip flag (e.g., pc cloud secrets set NAME --file.env --skip)

Cloud Build Path

This path uses Pipecat Cloud to build your Docker image from source. No local Docker installation is required.

Step 1: Verify Dockerfile and Lockfile

Check that a Dockerfile exists in the build context directory (the directory containing pcc-deploy.toml, or the context_dir from the [build] section of the config). If no Dockerfile is found, tell the user they need one and stop.

If the Dockerfile references uv (e.g., uv sync, uv pip install, COPY uv.lock), check that a uv.lock file exists in the build context directory. If it doesn't exist, run uv lock to generate it. If it already exists, run uv lock to ensure it's up to date. The lockfile must be present and current because cloud builds run remotely and cannot generate it.

Step 2: Secrets Setup

Ask the user if they need to create or update secrets for this deployment.

  • If yes, determine the env file path (from --env argument, or look for .env in the same directory as the config file, or ask the user).
  • Read the secret_set name from the pcc-deploy.toml configuration.
  • Run: pc cloud secrets set {SECRET_SET_NAME} --file {ENV_FILE_PATH} --skip
  • Show the output to the user.
  • If no, skip this step.

Step 3: Deploy

Ask the user to confirm they want to deploy the agent.

  • Show a summary of what will be deployed (agent_name, secret_set from the config).
  • Run from the config directory: pc cloud deploy --force
  • Use a generous timeout (10 minutes) as the cloud build and deployment can take a while.
  • This command handles both the cloud build and the deployment automatically.
  • If the command times out but no error occurred, retrieve the build ID from the command output and run pc cloud build logs {BUILD_ID} to check build progress. Share the output with the user.
  • If the build succeeds but deployment times out, check agent logs with pc cloud agent logs {AGENT_NAME} and share with the user.
  • Show the deployment output and status to the user.

Cloud Build Error Handling

  • If the build fails, retrieve the build ID from the command output and run pc cloud build logs {BUILD_ID} to show the user what went wrong.
  • Common cloud build issues:

- Missing or invalid Dockerfile - Build context too large (500MB limit) — check for large files that should be in .dockerignore - Build timeout — the build exceeded the maximum duration


Self-Managed Image Path

This path builds and pushes the Docker image from your machine. Requires Docker to be installed and running.

Step 1: Docker Prerequisites

Check these additional prerequisites:

  • Docker: Check if docker info succeeds (daemon running). If not, tell the user to start Docker and stop.
  • Docker login: Check if docker login succeeds. If not logged in, tell the user to run docker login and stop.

Step 2: Secrets Setup

Ask the user if they need to create or update secrets for this deployment.

  • If yes, determine the env file path (from --env argument, or look for .env in the same directory as the config file, or ask the user).
  • Read the secret_set name from the pcc-deploy.toml configuration.
  • Run: pc cloud secrets set {SECRET_SET_NAME} --file {ENV_FILE_PATH} --skip
  • Show the output to the user.
  • If no, skip this step.

Step 3: Build and Push Docker Image

Ask the user if they want to build and push the Docker image.

  • If yes:

- First, check if uv.lock exists in the config directory. If so, run uv lock to ensure it's up to date before building. - Run from the config directory: pc cloud docker build-push --force - Use a generous timeout (5 minutes) as builds can take a while. - If the build fails due to a stale lockfile, run uv lock in the config directory and retry. - If the build fails for other reasons, show the error and ask the user how to proceed.

  • If no, skip this step (image may already be pushed).

Step 4: Deploy

Ask the user to confirm they want to deploy the agent.

  • Show a summary of what will be deployed (agent_name, image, secret_set from the config).
  • Run from the config directory: pc cloud deploy --force
  • Use a generous timeout (5 minutes) as deployment may take time to reach ready state.
  • If deployment times out but no error occurred, check logs with pc cloud agent logs {AGENT_NAME} and share with the user — the deployment may still be starting up.
  • Show the deployment output and status to the user.

Self-Managed Image Error Handling

  • Common issues:

- Docker not logged in to the image registry (docker login) - Missing image field in pcc-deploy.toml - Stale uv.lock file — run uv lock to fix


General Error Handling

  • If any pc command fails, show the full error output and explain what might have gone wrong.
  • Common issues for both paths:

- Invalid or expired Pipecat Cloud authentication - Missing or malformed pcc-deploy.toml - Secret set name mismatch between config and what exists in Pipecat Cloud

Completion

After a successful deployment, summarize what was done:

  • Deployment method used (cloud build or self-managed image)
  • Secrets created/updated (if applicable)
  • Image built and pushed (if applicable)
  • Agent deployed with name from config

平台分布

Codex

35.65%
按下载量换算32

Claude

32.6%
按下载量换算29

Cursor

19.6%
按下载量换算18

Gemini CLI

9.45%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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