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automateautomate 自动化

Agent Skill

automate 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

51,286

周安装

2,095

GitHub Stars

2

下载量

16,425
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:automate(automate 自动化)
来源仓库:https://github.com/ivangdavila/automate
安装命令:
openclaw skills install automate
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install automate

简介

识别浪费代币的任务。脚本不会产生幻觉,不会产生每次运行成本,也不会随机失败。发现自动化机会并构建它们。

SKILL.md

name
Automate
description
Identify tasks that waste tokens. Scripts don't hallucinate, don't cost per-run, and don't fail randomly. Spot automation opportunities and build them.

Core Principle

LLMs are expensive, slow, and probabilistic. Scripts are free, fast, and deterministic.

Every time you do something twice that could be scripted, you're wasting:

  • Tokens — money burned on solved problems
  • Time — seconds/minutes vs milliseconds
  • Reliability — LLMs fail randomly, scripts fail predictably

Check signals.md for detection patterns. Check templates.md for common script patterns.


The Automation Test

Before doing any task, ask:

  1. Is this deterministic? Same input → same output every time?
  2. Is this repetitive? Will this happen again?
  3. Is this rule-based? Can I write down the exact steps?

If yes to all three → script it, don't LLM it.


Script vs LLM Decision Matrix

Task typeScriptLLM
Format conversion (JSON↔YAML)
Text transformation (regex)
File operations (rename, move)
Data validation
API calls with fixed logic
Git workflows
Judgement calls
Creative content
Ambiguous inputs
One-time unique tasks

Automation Triggers

When you notice yourself:

  • Doing the same task twice → script it
  • Writing similar prompts repeatedly → script the pattern
  • Formatting output the same way → script the formatter
  • Validating data with same rules → script the validator
  • Calling APIs with predictable logic → script the integration

Automation Proposal Format

When you spot an opportunity:

🔧 Automation opportunity

Task: [what you keep doing]
Frequency: [how often]
Current cost: [tokens/time per run]

Proposed script:
- Language: [bash/python/node]
- Input: [what it takes]
- Output: [what it produces]
- Location: [where to save it]

Estimated savings: [tokens/time saved per month]

Should I write it?

Script Standards

When writing automation:

  1. Single purpose — one script, one job
  2. Idempotent — safe to run multiple times
  3. Documented — usage in comments at top
  4. Logged — output what you're doing
  5. Fail loud — exit codes, error messages
  6. No secrets hardcoded — env vars or keychain

Tracking Automations

Document what you've built:

### Active Scripts
- scripts/format-json.sh — JSON prettifier [saved ~2k tokens/week]
- scripts/deploy-staging.sh — one-command deploy [saved 5min/deploy]
- scripts/sync-env.sh — env file sync [eliminated manual errors]

### Candidates
- Weekly report generation — repetitive formatting
- Log parsing — same grep patterns every time

The 3x Rule

If you do something 3 times, it must become a script.

  • 1st time: Do it, note that it might repeat
  • 2nd time: Do it, flag as automation candidate
  • 3rd time: Stop. Write the script first, then run it.

Anti-Patterns

Don'tDo instead
Re-prompt for same transformationWrite a script once
Use LLM for data validationWrite validation rules
Burn tokens on formattingUse formatters (prettier, jq, etc.)
Ask LLM to remember proceduresDocument in scripts
Solve same problem differently each timeStandardize with automation

*Every script written = permanent token savings. Compound your efficiency.*

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

79.6%
按下载量换算13,074

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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