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Agent Skill · 开发

deploy-verify(部署验证)

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-verify 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;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 16,944。

总安装 451周安装 19GitHub Stars 2下载 158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-verify(部署验证)
来源仓库:https://github.com/jonmumm/skills
仓库路径:skills/deploy-verify
安装命令:
npx skills add https://github.com/jonmumm/skills --skill deploy-verify
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/jonmumm/skills --skill deploy-verify

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。

部署 Cloudflare Workers 后自动推断变更内容并执行验证测试,确保功能正常。适用于 Codex、Claude、Cursor、Gemini CLI 中边缘函数发布,集成 pre-deploy 检查。从 git diff 提取修改范围,针对性运行健康检查与请求模拟,报告通过或异常。

安装命令为 npx skills add https://github.com/jonmumm/skills --skill deploy-verify。依赖 wrangler.toml 识别环境,未找到配置时将提示用户提供部署目标。

来源仓库内路径:skills/deploy-verify

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/jonmumm/skills --skill deploy-verify;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

    它需要接触敏感数据,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-verify 怎么安装?

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

deploy-verify 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-verify 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

deploy-verify 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-verify 用的人多吗?

公开数据是累计安装 451 次,近一周安装 19 次,下载 158 次,GitHub 2 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-verify 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

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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-verify

部署验证 · 本页

4512接触敏感数据未明确有提醒

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 & Verify

Deploy Cloudflare Workers to an environment and verify the changes work by inferring what to test from recent git changes.

Workflow

1. Pre-deploy checks
2. Deploy to target environment
3. Infer verification plan from git diff
4. Run verification
5. Report results (pass/flag issues)

Step 1: Pre-Deploy Checks

Before deploying, verify:

  1. Types pass — tsc --noEmit or project equivalent
  2. Tests pass — npm test / bun test / project equivalent
  3. No uncommitted changes — git status should be clean (warn if dirty)
  4. Detect environment config — read wrangler.toml / wrangler.jsonc for available environments
# List available environments from wrangler config
grep -E '^\[env\.' wrangler.toml | sed 's/\[env\.\(.*\)\]/\1/'

Step 2: Deploy

# To a named environment (staging, preview, etc.)
wrangler deploy --env <environment>

# To production (default if no --env)
wrangler deploy

If the project has multiple Workers (monorepo), detect which one changed:

  • Check git diff --name-only for paths matching Worker directories
  • Only deploy the Worker(s) that changed

Step 3: Infer Verification Plan

This is the key step. Look at what changed and determine what to verify:

# What changed since last deploy?
git diff HEAD~1 --name-only
git diff HEAD~1 --stat
git log HEAD~1..HEAD --oneline

Inference rules:

Change typeWhat to verify
API route handler changedHit that endpoint, check response shape and status
Middleware changedTest requests that flow through it
Auth logic changedTest both authenticated and unauthenticated requests
KV/D1/R2 bindings changedTest read/write operations on those bindings
Environment variables referencedVerify secrets are set: wrangler secret list --env <env>
CORS or headers changedCheck response headers
Error handling changedTest error paths
New route addedHit the new route, verify 200 + correct response
Route removedVerify it returns 404
Static assets changedFetch them and verify content

Step 4: Run Verification

Use curl or fetch to test the deployed URL:

# Basic health check
curl -s -o /dev/null -w "%{http_code}" https://<worker-url>/

# Check specific endpoint with response body
curl -s https://<worker-url>/api/endpoint | jq .

# Check response headers
curl -sI https://<worker-url>/api/endpoint

# POST with body
curl -s -X POST https://<worker-url>/api/endpoint \
  -H "Content-Type: application/json" \
  -d '{"key": "value"}'

Also check wrangler logs for errors after hitting endpoints:

# Tail logs (run in background, hit endpoints, then check)
wrangler tail --env <environment> --format json

Step 5: Report

If all checks pass:

Deploy verified:
- Environment: staging
- URL: https://my-worker-staging.example.workers.dev
- Checks passed:
  - GET /api/stories → 200, response shape correct
  - POST /api/generate → 200, returns stream
  - KV read/write → working

If issues found (flag, don't rollback):

Deploy issues found:
- Environment: staging
- URL: https://my-worker-staging.example.workers.dev
- PASS: GET /api/stories → 200
- FAIL: POST /api/generate → 500
  - Error in logs: "Missing AI binding"
  - Likely cause: AI binding not configured in staging env
- Action needed: Check wrangler.toml [env.staging] AI bindings

Do NOT automatically rollback. Flag the issues and let the user decide.

Multi-Environment Patterns

Common setup:

# wrangler.toml
name = "my-worker"

[env.staging]
name = "my-worker-staging"
route = "staging.example.com/*"

[env.production]
name = "my-worker"
route = "example.com/*"

Default flow: Deploy to staging → verify → user promotes to production. Direct to prod: Only when user explicitly asks. Still run verification after.

Secrets

If verification fails with auth/config errors, check that secrets match between environments:

wrangler secret list --env staging
wrangler secret list --env production

Secrets don't copy between environments. A common gotcha after adding a new env.

Troubleshooting

ProblemFix
500 after deploywrangler tail --env <env> to see error logs
Binding not foundCheck wrangler.toml — bindings must be declared per environment
Secret missingwrangler secret put <NAME> --env <env>
Old code still servingWorker may be cached — wait 30s or check wrangler deployments list
Route not matchingVerify route patterns in wrangler.toml match the URL you're hitting
CORS errorsCheck if the Worker sets appropriate CORS headers for the origin

Gotchas

  • Always verify the deployed version matches your expected commit. Run wrangler deployments list to confirm your code actually deployed. Cached old versions are a common false trail.
  • Don't strip console.log in production builds. You need logs for debugging — if you can't see what's happening, you can't fix what's broken. Keep logging in production, especially during early development.
  • Secrets don't copy between environments. Adding a secret to production doesn't add it to staging. After creating a new environment, run wrangler secret list --env <env> to verify ALL required secrets are set.
  • Check both .dev.vars AND GitHub Actions secrets. They are independent — a secret in .dev.vars only works locally. GH Actions needs its own secrets configured.
  • Deployed URL might not match what you expect. If using custom domains, verify the route pattern in wrangler.toml matches the URL you're testing. Preview deployments use different URLs than production.
  • After deploy, wait 30 seconds before testing. Workers edge cache can serve stale responses briefly. If you see old behavior, wait and retry before debugging.

平台分布

Codex

35.22%
按下载量换算56

Claude

32.87%
按下载量换算52

Cursor

18.94%
按下载量换算30

Gemini CLI

9.98%
按下载量换算16

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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