AgentHubAgentHub

automation Skill Install & Guide

SkillSkillsMP

io.github.proma-ai/Proma/automation

Proma 内嵌自动任务与定时任务 Skill,属于 Proma 自带能力而不是用户临时安装的外部 Skill。触发要非常宽泛、非常冗余:只要用户的话里出现任何“未来还要做”“以后继续看”“重复做”“再跑一次也有价值”“定期/周期/每天/每周/每月/每隔一段时间”“持续关注/持续观察/长期跟进/长期监控”“自动检查/自动汇总/自动生成/自动复盘/自动维护”“无人值守”“有变化告诉我”“异常时提醒我”“结果不好就调整”“查看运行记录”“优化已有任务”“暂停/恢复/删除/立即运行任务”等迹象,就应该触发此 Skill,先判断是否适合 Proma 定时任务。也要覆盖一次性与有限次的延时执行信号:“X 小时/天后跑一次”“过一会儿/晚点/稍后自动做”“到某个具体时间点执行一次”“跑几次/连续观察 N 次就停”——这类未来无人值守的延时任务现在同样适合 Proma 定时任务(用 once 或 maxRuns),不要再一概当成不支持。模糊场景也可以触发:例行报告、日报周报、项目状态、GitHub/邮件/飞书/文件/发布/CI/价格/竞品/数据源的反复检查,重复研究流程,定期整理知识,自动化工作流维护。高频触发不代表必须创建任务;纯提醒/闹钟/倒计时、需要用户实时参与判断、或结果没有任何留存价值的事,要明确说明不推荐创建 Proma 定时任务,并给出替代做法。

Copy the install config on this page first, then verify docs and permissions upstream.

Popularity

Repo stars1.5k

Overview

Proma 内嵌自动任务与定时任务 Skill,属于 Proma 自带能力而不是用户临时安装的外部 Skill。触发要非常宽泛、非常冗余:只要用户的话里出现任何“未来还要做”“以后继续看”“重复做”“再跑一次也有价值”“定期/周期/每天/每周/每月/每隔一段时间”“持续关注/持续观察/长期跟进/长期监控”“自动检查/自动汇总/自动生成/自动复盘/自动维护”“无人值守”“有变化告诉我”“异常时提醒我”“结果不好就调整”“查看运行记录”“优化已有任务”“暂停/恢复/删除/立即运行任务”等迹象,就应该触发此 Skill,先判断是否适合 Proma 定时任务。也要覆盖一次性与有限次的延时执行信号:“X 小时/天后跑一次”“过一会儿/晚点/稍后自动做”“到某个具体时间点执行一次”“跑几次/连续观察 N 次就停”——这类未来无人值守的延时任务现在同样适合 Proma 定时任务(用 once 或 maxRuns),不要再一概当成不支持。模糊场景也可以触发:例行报告、日报周报、项目状态、GitHub/邮件/飞书/文件/发布/CI/价格/竞品/数据源的反复检查,重复研究流程,定期整理知识,自动化工作流维护。高频触发不代表必须创建任务;纯提醒/闹钟/倒计时、需要用户实时参与判断、或结果没有任何留存价值的事,要明确说明不推荐创建 Proma 定时任务,并给出替代做法。 automation is a Agent Skill listed from SkillsMP. This page includes an overview, setup tutorial, install commands, and use cases for Trae, Tongyi Lingma, Cursor, Claude Code, and VS Code.

Use cases

AgentHub Verified AvailabilityTested & Ready

Automated pipeline validated install commands, protocol & client compatibility

Verified At2026-07-18
Install Snippets TestedCLI & JSON config syntax verified
Protocol Handshake ReadyComplies with JSON-RPC 2.0 specifications
Origin Registry ActiveSourced from skillsmp
Verified ClientsClaude Code、Claude Desktop、Cursor 等
Security Tier: A+ 级 · 零权限本地沙盒 (A+)·Scanned for high-risk vulnerabilities. Recommended to run with project-scoped permissions.

Send this prompt to your AI to install the Skill

Recommended
Target client (auto-optimizes prompt):
PROMPT >

Follow the install guide at https://myagenthub.cn/install/skill.md?lang=en to automatically detect the current IDE and install the skill "proma-ai/Proma@automation" without asking, and tell me how to verify it afterwards.

💡Paste into your AI coding assistant (Cursor, Trae, Claude Code) — the agent will handle download and configuration automatically.

Copy by platformAlternative

Choose your platform

Choose install method

Click to copy snippet
# 改 -a 切换客户端:trae | lingma | codebuddy | kimi-code-cli | qwen-code | cursor | claude-code | windsurf | cline | github-copilot | codex
npx skills add proma-ai/Proma@automation -a cursor -y

Setup tutorial

  1. Open the automation page and confirm the source is SkillsMP.
  2. Copy the install command for Trae, Lingma, Cursor, Claude Code, or universal CLI.
  3. Run it, or place SKILL.md under .trae/skills/, .lingma/skills/, or .cursor/skills/.
  4. Reload the client, then describe your task so the agent can match this skill.

Install commands

Install commands and setup steps are in the HTML so search engines and no-JS browsers can read them without running client JavaScript.

Universal — Skills CLI (recommended)

Skills CLI

# 改 -a 切换客户端:trae | lingma | codebuddy | kimi-code-cli | qwen-code | cursor | claude-code | windsurf | cline | github-copilot | codex
npx skills add proma-ai/Proma@automation -a cursor -y

AgentHub CLI (change --ai)

# 改 --ai 切换客户端:trae | lingma | workbuddy | kimi | qwen | cursor | claude-code | windsurf | cline | vscode | codex | openclaw
curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init proma-ai/Proma@automation --ai cursor -y

Cursor

Skills CLI

npx skills add proma-ai/Proma@automation -a cursor -y

AgentHub CLI (change --ai)

curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init proma-ai/Proma@automation --ai cursor -y

Project directory

mkdir -p .cursor/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o .cursor/skills/automation/SKILL.md
# 如有 scripts/ references/ assets/ 请一并复制

User directory

mkdir -p ~/.cursor/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o ~/.cursor/skills/automation/SKILL.md

Trae (ByteDance)

  1. Trae natively supports Skill specs: project-level in .trae/skills/<name>/, global in ~/.trae/skills/
  2. Copy and run the command in your project terminal to download SKILL.md
  3. Reload Trae window, then describe your task in AI chat to activate automatically

Skills CLI

npx skills add proma-ai/Proma@automation -a trae -y

AgentHub CLI (change --ai)

curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init proma-ai/Proma@automation --ai trae -y

Project directory

mkdir -p .trae/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o .trae/skills/automation/SKILL.md

User directory

mkdir -p ~/.trae/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o ~/.trae/skills/automation/SKILL.md

Tongyi Lingma (Alibaba)

  1. Tongyi Lingma supports skills in project .lingma/skills/<name>/ or global ~/.lingma/skills/
  2. Run the command to install SKILL.md
  3. In Lingma Agent mode, prompt your task and the skill will be automatically loaded

Skills CLI

npx skills add proma-ai/Proma@automation -a lingma -y

AgentHub CLI (change --ai)

curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init proma-ai/Proma@automation --ai lingma -y

Project directory

mkdir -p .lingma/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o .lingma/skills/automation/SKILL.md

User directory

mkdir -p ~/.lingma/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o ~/.lingma/skills/automation/SKILL.md

WorkBuddy / CodeBuddy (Tencent)

  1. WorkBuddy reads skills only from .workbuddy/skills/<name>/ (user-level ~/.workbuddy/skills/); .codebuddy/skills/ belongs to CodeBuddy
  2. The Skills CLI command installs with -a codebuddy and appends a copy step into .workbuddy/skills
  3. AgentHub CLI (--ai workbuddy) syncs it for you; reload the chat panel so the skill gets indexed

Skills CLI

npx skills add proma-ai/Proma@automation -a codebuddy -y
# WorkBuddy 读取 .workbuddy/skills,把上游写入 .codebuddy/skills 的结果同步一份
mkdir -p .workbuddy/skills && cp -R .codebuddy/skills/automation .workbuddy/skills/

AgentHub CLI (change --ai)

curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init proma-ai/Proma@automation --ai workbuddy -y

Project directory

mkdir -p .workbuddy/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o .workbuddy/skills/automation/SKILL.md

Claude Code

Project directory

mkdir -p .claude/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o .claude/skills/automation/SKILL.md

User directory

mkdir -p ~/.claude/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o ~/.claude/skills/automation/SKILL.md

Skills CLI

npx skills add proma-ai/Proma@automation -a claude-code -y

Kimi Code (Moonshot AI)

  1. Kimi Code supports standard Agent Skills: project-level in .agents/skills/<name>/, global in ~/.agents/skills/
  2. Run the command to install
  3. In Kimi Code CLI, describe your task to trigger the skill

Skills CLI

npx skills add proma-ai/Proma@automation -a kimi-code-cli -y

AgentHub CLI (change --ai)

curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init proma-ai/Proma@automation --ai kimi -y

Project directory

mkdir -p .agents/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o .agents/skills/automation/SKILL.md

User directory

mkdir -p ~/.agents/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o ~/.agents/skills/automation/SKILL.md

Qwen Code (Alibaba)

  1. Qwen Code supports project .qwen/skills/<name>/ and global ~/.qwen/skills/
  2. Run the command to deploy SKILL.md
  3. Prompt the agent to trigger the skill

Skills CLI

npx skills add proma-ai/Proma@automation -a qwen-code -y

AgentHub CLI (change --ai)

curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init proma-ai/Proma@automation --ai qwen -y

Project directory

mkdir -p .qwen/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o .qwen/skills/automation/SKILL.md

User directory

mkdir -p ~/.qwen/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o ~/.qwen/skills/automation/SKILL.md

Windsurf

  1. Windsurf supports project-level .windsurf/skills/<name>/ or global ~/.codeium/windsurf/skills/
  2. Run the install command and refresh Cascade
  3. Cascade will auto-activate the skill based on its description

Skills CLI

npx skills add proma-ai/Proma@automation -a windsurf -y

AgentHub CLI (change --ai)

curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init proma-ai/Proma@automation --ai windsurf -y

Project directory

mkdir -p .windsurf/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o .windsurf/skills/automation/SKILL.md

User directory

mkdir -p ~/.codeium/windsurf/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o ~/.codeium/windsurf/skills/automation/SKILL.md

Cline

  1. Cline supports standard .agents/skills/<name>/ structure
  2. Run the command to install the skill
  3. Ask questions in the Cline panel to trigger the skill

Skills CLI

npx skills add proma-ai/Proma@automation -a cline -y

AgentHub CLI (change --ai)

curl -fsSL "https://myagenthub.cn/cli/agenthub-skill.mjs" | node --input-type=module - init proma-ai/Proma@automation --ai cline -y

Project directory

mkdir -p .agents/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o .agents/skills/automation/SKILL.md

Cherry Studio

  1. Use this skill as an Assistant system prompt in Cherry Studio
  2. Copy the command to view SKILL.md text
  3. Paste the contents into Cherry Studio Assistant system prompt
# 打印 SKILL.md 指令内容并粘贴到 Cherry Studio 智能体系统提示词中
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md"

VS Code / GitHub Copilot

mkdir -p .github/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o .github/skills/automation/SKILL.md

OpenAI Codex

Skills CLI

npx skills add proma-ai/Proma@automation -a codex -g -y

User directory

mkdir -p ~/.codex/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o ~/.codex/skills/automation/SKILL.md

Project directory

mkdir -p .agents/skills/automation
RAW="https://raw.githubusercontent.com/proma-ai/Proma/main/apps/electron/default-skills/automation"
curl -sL "$RAW/SKILL.md" -o .agents/skills/automation/SKILL.md

Troubleshooting & Common ErrorsFAQ

Common connection errors and verified fixes for automation

Getting 'connection closed' or exit code 1 in Cursor / Claude Code for automation?

Usually caused by missing runtime paths or IDE environment inheritance. Fix steps: 1. Verify Node.js 18+ (npx) or Python 3.10+ (uvx) is installed; 2. Run 'which npx' or 'which uvx' in terminal, and replace 'command' with absolute path; 3. Reload or restart the client window after modifying config.

Fix Snippet
# Check binary path in terminal:
which npx
node -v
Getting 'spawn npx ENOENT' or 'command not found'?

The editor background process does not inherit your full terminal PATH. Solution: Globally install the package, or set the absolute binary path (e.g. C:\Program Files\nodejs\npx.cmd on Windows, or /usr/local/bin/npx on macOS).

Tool calls timing out or failing to download packages?

First-time package downloading might be slow or timeout due to network limits. Configure a reliable mirror or check outbound proxy settings.

Agent does not match or apply automation during conversations?

Verify SKILL.md is located at .cursor/skills/automation/SKILL.md (Cursor) or ~/.claude/skills/automation/SKILL.md (Claude Code). You can explicitly mention the skill name in your prompt to boost match confidence.

Tool Mock Playground

Sandbox

automation Rule Injection & Agent Behavior Simulation · Preview tool schema & outputs without local runtime

Sandbox Ready
fn: agent_skill_runtimeInject system prompt guidelines & workflow constraints from automation
Request ArgumentsJSON Schema
{
  "skill": "automation",
  "rulePath": ".cursor/skills/automation/SKILL.md",
  "userGoal": "请使用 automation 的方法与标准帮我完成当前任务",
  "client": "Cursor / Claude Code"
}
💡Parameters generated dynamically by Agent runtime
Agent Tool Output

Click 'Run Mock' above

to preview the raw response returned to the LLM

Env: AgentHub Virtual SandboxJSON-RPC 2.0

Decision Guide: Why & When to Use

Assess suitability before installing to save trial-and-error time

Best Suited For
  • PR review
  • Changelog generation
  • Cross-repo issue search
When NOT to Use
  • Replacing human security audit
  • Unauthorized repo access
Recommended Workflow Pairing:View Scenario →

automation + Scenario Prompt → Complete Agent Automation

Skill hands-on: install to visible results

Follow the full lab (expected UI/output + contrast checks). After installing this item, verify with the tutorial prompts.

Open tutorial →

An Agent Skill is a folder with SKILL.md instructions. After install, the AI loads it automatically when your task matches its description.

How to use

After installing, describe your task in chat (or mention the skill name). The agent reads the skill description to decide when to activate it, then follows the instructions in SKILL.md. Check loaded skills via /skills in Claude Code or in your client settings.

Related resources

Planning with files

v3.23.0

SkillClawHub44.6k

io.clawhub.othmanadi/planning-with-files

Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and emits aggregate counts only; --replay may emit bounded nonce-framed excerpts. Optional gated mode can request continuation only when the host supports it and never runs commands declared in Markdown. The skill has no network upload path. Use for research or work needing 5+ tool calls.

source

ClawCall

v2.0.1

SkillClawHub53.1k

io.clawhub.clawcall-dev/clawcall-dev

Use when the user wants an AI agent to place a US phone call, call a business, handle hold or phone menus, confirm/reschedule/cancel/book/follow up/check an order, reach a real person, leave voicemail, connect the user into a live call, configure ClawCall voice/personality/profile or inbound reserved-number answering, poll received inbound calls, or link a ClawCall API key. Not for SMS, email, or international calls.

source

中文公文写作

v2.0.25

SkillClawHub9.1k

io.clawhub.gongyu0918-debug/chinese-official-writing

用于中文公文、事务性材料和新闻稿件的起草、改写、压缩、润色、审校、文种核对、去口语化、降 AI 味及 Word 格式处理,适用于机关、企事业单位、学校和新闻机构。涵盖申请、请示、报告、通知、通告、意见、决定、决议、议案、公报、命令、函、复函、批复、说明、方案、纪要、公告、公示、通报、制度、规定、办法、细则、操作规程、工作要点、总结、调研、讲话、致辞、主持词、述职、可研、审查材料、技术需求、新闻消息、编者按、新闻评论,以及采购、整改、反馈和 AI 算力等场景。

source

Often paired with

Keep exploring AgentHub

Most people compare similar tools or check scenario guides before installing—start here.

Listing badge: put AgentHub on your site

Copy either snippet into your project homepage, docs, or GitHub README. The badge is a hotlinked SVG — nothing to host — and it links back to this page so visitors can find the install steps.

PreviewListed on AgentHub: automation
HTML
<a href="https://myagenthub.cn/p/io.github.proma-ai/Proma/automation" title="Listed on AgentHub: automation" target="_blank" rel="noopener">
  <img src="https://myagenthub.cn/badge/io.github.proma-ai/Proma/automation?lang=en" alt="Listed on AgentHub: automation" height="20" style="border:0"/>
</a>
Markdown (GitHub README)
[![Listed on AgentHub: automation](https://myagenthub.cn/badge/io.github.proma-ai/Proma/automation?lang=en)](https://myagenthub.cn/p/io.github.proma-ai/Proma/automation)

Badges are generated on the fly from /badge/<package-id>, so name and listing changes propagate automatically. Keep the link target unchanged — it is what counts as the referral.

Unified Manifest

{
  "id": "io.github.proma-ai/Proma/automation",
  "type": "skill",
  "version": "main",
  "displayName": "automation",
  "description": "Proma 内嵌自动任务与定时任务 Skill,属于 Proma 自带能力而不是用户临时安装的外部 Skill。触发要非常宽泛、非常冗余:只要用户的话里出现任何“未来还要做”“以后继续看”“重复做”“再跑一次也有价值”“定期/周期/每天/每周/每月/每隔一段时间”“持续关注/持续观察/长期跟进/长期监控”“自动检查/自动汇总/自动生成/自动复盘/自动维护”“无人值守”“有变化告诉我”“异常时提醒我”“结果不好就调整”“查看运行记录”“优化已有任务”“暂停/恢复/删除/立即运行任务”等迹象,就应该触发此 Skill,先判断是否适合 Proma 定时任务。也要覆盖一次性与有限次的延时执行信号:“X 小时/天后跑一次”“过一会儿/晚点/稍后自动做”“到某个具体时间点执行一次”“跑几次/连续观察 N 次就停”——这类未来无人值守的延时任务现在同样适合 Proma 定时任务(用 once 或 maxRuns),不要再一概当成不支持。模糊场景也可以触发:例行报告、日报周报、项目状态、GitHub/邮件/飞书/文件/发布/CI/价格/竞品/数据源的反复检查,重复研究流程,定期整理知识,自动化工作流维护。高频触发不代表必须创建任务;纯提醒/闹钟/倒计时、需要用户实时参与判断、或结果没有任何留存价值的事,要明确说明不推荐创建 Proma 定时任务,并给出替代做法。",
  "author": {
    "name": "proma-ai",
    "url": "https://github.com/proma-ai"
  },
  "repository": {
    "url": "https://github.com/proma-ai/Proma",
    "source": "github",
    "subfolder": "apps/electron/default-skills/automation"
  },
  "homepage": "https://skillsmp.com/creators/proma-ai/proma/apps-electron-default-skills-automation",
  "distribution": {
    "packages": [
      {
        "registryType": "source",
        "identifier": "proma-ai/Proma@automation",
        "version": "main",
        "runtimeHint": "npx skills add"
      }
    ],
    "remotes": []
  },
  "dependencies": [],
  "installTargets": [
    "claude-code",
    "claude-desktop",
    "cursor",
    "codex",
    "vscode"
  ],
  "keywords": [
    "repo_stars:1515"
  ],
  "provenance": {
    "origin": "skillsmp",
    "originalId": "proma-ai-proma-apps-electron-default-skills-automation-skill-md",
    "originalUrl": "https://skillsmp.com/creators/proma-ai/proma/apps-electron-default-skills-automation",
    "isOfficial": false,
    "status": "active"
  }
}
automation Skill Install & Guide - AgentHub