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Agent Skill · 研究检索

computer-task-execution(计算机任务执行)

computer-task-execution 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

computer-task-execution 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为操作浏览器;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 31,031。

总安装 2,775周安装 118GitHub Stars 公开资料未说明下载 972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
MIT-0
版本
1.0.0

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:computer-task-execution(计算机任务执行)
来源仓库:https://github.com/gift-is-coding/computer-task-execution
安装命令:
openclaw skills install computer-task-execution
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 computer-task-execution

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

使用具有验证和学习模式的最可靠、侵入性最小的方法在网站或本地应用程序上执行多步骤用户任务。

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 OpenClaw;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 openclaw skills install computer-task-execution;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

computer-task-execution 怎么安装?

在终端执行 openclaw skills install computer-task-execution。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

computer-task-execution 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

computer-task-execution 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。

computer-task-execution 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

computer-task-execution 用的人多吗?

公开数据是累计安装 2,775 次,近一周安装 118 次,下载 972 次。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。

computer-task-execution 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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 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 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
computer-task-execution

计算机任务执行 · 本页

2,775—操作浏览器MIT-0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

name
computer-task-execution
description
Execute real user tasks across websites and local applications with a reliability-first strategy. Use when the user wants the agent to actually do something, not just answer: operate a website, complete a flow in a desktop app, send a message, edit content in a GUI, retrieve information from an app, or finish a multi-step computer task. Especially use when deciding between browser execution, app scripting, local UI automation, or low-intrusion execution paths.

computer-task-execution

Core idea

Execute the task, not the interface.

Start from the user goal and choose the path with the best combination of:

  • success rate
  • verifiability
  • low user disruption
  • low repeated trial-and-error

Do not default to local GUI automation. Prefer interfaces that are easier to verify and less intrusive.

Golden rules

  1. Prefer reliability over cleverness. A short visible foreground step is better than an invisible but flaky flow.
  2. Prefer data/interface layers over GUI simulation. If an API, scriptable interface, URL scheme, local file, browser DOM, or official automation surface exists, use that before UI driving.
  3. Prefer browser execution over local-app execution when the same task can be done on the web with adequate login state and verification.
  4. Treat verification as part of execution. A task is not done until the result is checked using the most reliable available evidence.
  5. Minimize focus stealing, but do not worship zero-focus-steal. The correct target is minimum user disruption with high confidence, not purity.
  6. Reuse proven patterns. Once a path has succeeded for a software target or domain, record it and use it first next time.

Decision model

Before acting, classify the task:

A. Read-only task

Examples:

  • read meeting details
  • inspect app state
  • fetch notifications
  • extract page content
  • check whether something exists

Default preference:

  1. browser/web task path
  2. local files / local database / app-exported data
  3. official scripting interface
  4. local app UI automation

B. Write-without-send task

Examples:

  • create a draft
  • fill a form but do not submit yet
  • edit a spreadsheet
  • prepare a document
  • populate a field

Default preference:

  1. browser/web task path
  2. official scripting / URL scheme / file-based write
  3. local app UI automation with minimum foreground time

C. High-risk action task

Examples:

  • send a message
  • submit a form
  • delete or modify live data
  • post to social media
  • trigger an approval flow

Default preference:

  1. browser/web task path if reliable and verifiable
  2. official app interface if supported and verifiable
  3. local app UI automation with explicit pre-check and post-check

For high-risk actions, if correct targeting depends on visible UI state, expect foreground execution for the critical step.

Execution-path priority

Always try paths in this order unless the task or accumulated target knowledge strongly suggests otherwise:

  1. Browser/web execution

- Best when the target service is available on the web - Prefer DOM-visible, page-verifiable flows - Best default for logged-in services when browser access is available

  1. Official non-UI interface

- App scripting - URL schemes - built-in automation hooks - import/export surfaces - local data files or supported storage

  1. Hybrid execution

- Prepare in background using data or browser - Switch to foreground only for the minimum critical action window - Immediately verify and exit

  1. Local app UI automation

- Use only when the task cannot be completed more reliably elsewhere - Prefer keyboard-first flows only when target focus can be guaranteed - Use visual or state verification for completion

  1. Background/local no-focus experimentation

- Last resort for low-risk tasks or explicit user request - Treat as experimental unless already proven for this target - If success is not strongly verifiable, do not present it as complete

Focus policy

When background/no-focus execution is appropriate

Prefer trying no-focus or low-focus execution when:

  • the task is read-only
  • the action operates on data rather than UI state
  • the target exposes a scriptable surface
  • verification does not depend on visible window state
  • the user explicitly requests silent/minimal-disruption mode

When foreground execution is usually necessary

Use foreground execution for the critical step when:

  • keyboard input must reach a specific target window or field
  • the result depends on visible UI state
  • recipient/target selection must be visually confirmed
  • the task sends, submits, deletes, or approves something
  • previous background attempts for this target were flaky

Preferred compromise

For local app tasks, default to:

  1. background preparation
  2. shortest possible foreground critical section
  3. post-action verification
  4. return control promptly

This is usually better than forcing a fully background flow.

Verification rules

Use the strongest available verification method:

  1. target-system confirmation

- message appears in thread - record exists - page shows success state - saved content is readable from source

  1. direct state read-back

- reread the object after write - check the updated field value - reload and confirm persistence

  1. visual confirmation

- screenshot or visible state inspection - only acceptable when stronger read-back is unavailable

  1. process-only confirmation

- use only for low-risk tasks - “command ran” is not sufficient evidence for a high-risk task

If you cannot verify confidently, say so and keep the result provisional.

Pattern memory: learn per software target

After each successful or meaningfully failed execution, update target-specific experience. If a relevant pattern already exists, reading it before execution is mandatory.

Storage

  • Website/domain patterns: references/site-patterns/<domain>.md
  • Local app patterns: references/site-patterns/<app-name>.md

What to record

Record only facts learned through execution:

  • successful path
  • required preconditions
  • whether foreground was necessary
  • whether browser was superior to app
  • known unstable paths
  • verification method that worked
  • date of discovery

Why this matters

Next time, if the target matches a known app or domain:

  1. read that pattern file first
  2. reuse the proven path first
  3. skip previously disproven paths unless the environment changed

This avoids repeated “try everything again” behavior.

Pattern file format

---
kind: local-app | website
name: WeChat
domain: x.com
app_id: com.tencent.xinWeChat
aliases: [微信, WeChat]
updated: 2026-03-27
---

## Successful paths
- [2026-03-27] Foreground: open -a WeChat → Command+F → paste contact → Enter → paste message → Enter

## Preconditions
- Main window present
- Search accepts pasted contact names

## Verification
- Sent message visibly appears in the target thread

## Unstable or failed paths
- [2026-03-27] Background-only keyboard injection was not reliably targetable

## Recommended default
- Use background preparation + short foreground execution + post-send verification

How to use pattern memory

Step 1: identify the target

Normalize the target to either:

  • a domain, or
  • an application name

Step 2: check for prior knowledge

If a matching pattern file exists, you must read it before choosing the execution path. Do not skip this step just because you already have a generic plan.

Step 3: start with the proven route

If the stored preferred route still fits the current request, use it first. Treat stored successful patterns as the default starting point.

Step 4: only explore when needed

Explore alternatives only if:

  • the preferred route fails
  • the user requested a different mode
  • the environment clearly changed
  • the stored pattern is clearly inapplicable to the current task

Do not re-run previously disproven paths unless there is a specific reason.

Step 5: update after execution

If new facts were learned, update the pattern file. Pattern memory is part of task completion, not optional cleanup.

Choosing browser vs local app

Prefer browser when

  • the service has a working web app
  • login state exists in browser
  • DOM/state inspection improves confidence
  • you need robust, repeatable verification
  • avoiding frontmost app disruption matters

Prefer local app when

  • the task is app-only
  • the app exposes better native automation than the website
  • the browser version is missing key capabilities
  • the task is already known to work reliably through a stored app pattern

Local app operating style

If local app execution is necessary, prefer this sequence:

  1. Determine exact success criteria
  2. Prepare all inputs before touching the app
  3. Open or locate the target app/window
  4. Keep foreground time as short as possible
  5. Execute only the critical path
  6. Verify immediately
  7. Record the winning pattern

Handling silent mode requests

If the user asks to avoid stealing focus:

  • first see whether browser or non-UI paths can satisfy the task
  • if local-app background execution is only partially reliable, say so internally in planning and choose it only when the task risk is low or the user explicitly prefers silence over certainty
  • for high-risk tasks, recommend minimum-foreground execution rather than pretending a background path is equally safe

Failure handling

When a path fails:

  1. identify whether the failure was due to targeting, focus, auth, UI drift, missing permissions, or bad path choice
  2. switch to the next-best path class instead of repeating the same failing method blindly
  3. if the failure teaches something reusable, record it in the target pattern file

References

  • Read references/pattern-memory.md for the pattern-memory policy.
  • Read references/site-patterns/<target>.md when a known software target or domain already has stored experience.

平台分布

OpenClaw

91.01%
按下载量换算885

安全审计

VirusTotal

未展示

ClawScan

可疑

Static analysis

通过

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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