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Agent Skill · 开发

auto-login-assistant(自动登录助手)

auto-login-assistant 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。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。

auto-login-assistant 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,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 3,509。

总安装 11,114周安装 454GitHub Stars 公开资料未说明下载 3,559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
0.1.0

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:auto-login-assistant(自动登录助手)
来源仓库:https://github.com/ddmmddmm/auto-login-assistant
安装命令:
openclaw skills install auto-login-assistant
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 auto-login-assistant

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。

auto-login-assistant 用于补充开发相关能力,适合在 OpenClaw 中承接开发任务时使用。支持登录状态检测与表单填写,适用于从登录墙恢复访问。

通过 clawhub 安装,命令为 openclaw skills install auto-login-assistant,需结合来源仓库进一步确认具体用法。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操作。当前功能描述基于原始 README,实际能力以官方文档为准。

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 auto-login-assistant;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

auto-login-assistant 怎么安装?

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

auto-login-assistant 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。

auto-login-assistant 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。

auto-login-assistant 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。

auto-login-assistant 用的人多吗?

公开数据是累计安装 11,114 次,近一周安装 454 次,下载 3,559 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。

auto-login-assistant 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

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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
auto-login-assistant

自动登录助手 · 本页

11,114—接触敏感数据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
auto-login-assistant
description
Help the agent recover from login walls on websites by detecting sign-in states, collecting user-approved credentials, filling common login forms, and handling verification codes safely. Use when browsing is blocked by authentication and the user wants guided sign-in rather than manual step-by-step help.
metadata
short-description
Detect login walls, fill credentials, and handle OTP safely.

Auto Login Assistant

Overview

Use this skill when the agent is navigating a website and progress is blocked by a login screen, expired session, or verification-code challenge. The skill provides a conservative workflow for sign-in assistance: detect the login wall, collect user-approved credentials, fill the form, and handle one-time codes with clear consent boundaries.

This skill is intentionally not a bypass tool. It should never attempt to break captchas, defeat anti-bot systems, or infer secrets the user did not explicitly provide.

When To Use

Trigger this skill when any of the following are true:

  • The page redirects to a login, sign-in, or session-expired screen.
  • The user asks the agent to sign in to a website, mailbox, SaaS product, or admin console.
  • A workflow such as reading email, sending mail, checking dashboards, or accessing settings is blocked by authentication.
  • The user wants the agent to help retrieve or place a verification code after they approve the flow.

Do not use this skill for:

  • Captcha solving, QR login bypass, hardware key prompts, payment approval, or biometric confirmation
  • Guessing usernames, passwords, security questions, or backup codes
  • Reading email or messages unless the user explicitly authorizes it for the current task

Workflow

1. Confirm It Is A Login Barrier

First verify that the page is actually asking for authentication. Look for signals such as:

  • URL patterns like login, signin, auth, session-expired, verify
  • Password fields, OTP fields, or email/username inputs
  • Buttons or headings such as "Sign in", "Log in", "Continue with email", "Enter code"

If the page is ambiguous, say so and ask the user whether you should treat it as a login flow before entering any credentials.

2. Choose Credential Source

Credential priority order:

  1. Credentials the user provides in the current conversation
  2. A local file path the user explicitly points to
  3. Environment variables the user explicitly names

Never scan the filesystem broadly for secrets. Never assume a saved credential source without user direction.

If the user gives a file path or env var name, use scripts/read_credentials.py to normalize it into a consistent structure.

Supported normalized fields:

  • site
  • login_url
  • username
  • email
  • phone
  • password
  • otp_email
  • otp_mode
  • notes

See references/config-example.md for examples.

3. Fill The Login Form Conservatively

Use the website's visible login flow rather than forcing a direct post.

Preferred field mapping order:

  • User identifier: email, username, account, phone
  • Secret: password
  • Verification: otp, code, verification code, security code

Before submitting:

  • Confirm the target site with the user if multiple accounts could apply
  • Mask secrets in your explanation
  • Avoid clicking "remember this device" or equivalent unless the user explicitly asks

4. Handle Verification Codes

Default behavior: ask the user to provide the verification code manually.

Only enter the email-reading branch if the user explicitly authorizes it for the current task and provides the mailbox access path. When allowed:

  • Read only the minimum mailbox content needed to locate the latest relevant code
  • Extract likely codes with scripts/extract_verification_code.py
  • Present the candidate briefly if confidence is low
  • If multiple codes are plausible, ask before submitting

If email access fails or is unavailable, fall back to asking the user to paste the code.

5. Validate Success

After submit, confirm login success using page evidence:

  • User avatar, account menu, inbox, dashboard, or "sign out" control
  • Removal of login prompt
  • Successful navigation to the requested feature

If the flow fails, stop after a small number of attempts and explain the blocker clearly. Do not loop forever on retries.

Safety Rules

  • Treat credentials as ephemeral unless the user explicitly asks for a reusable local config.
  • Do not store credentials in the skill folder.
  • Do not broaden permissions, change MFA settings, or approve trusted-device prompts without explicit user permission.
  • Refuse flows that amount to bypassing authentication or anti-abuse protections.
  • If the website requests a captcha, QR scan, physical token, or passkey confirmation, hand control back to the user.

Suggested Interaction Pattern

Use short, direct prompts like these:

  • "This page appears to require login. Do you want me to sign in with credentials you provide now, or a local config you specify?"
  • "I found a password field and an email field. Please provide the account for this site, or point me to the config path."
  • "The site is asking for a verification code. If you want, paste the code here. I can only read email for this if you explicitly authorize that mailbox for this task."

Resources

references/config-example.md

Load this when the user wants a reusable local credential format or wants to see supported fields.

scripts/read_credentials.py

Run this to normalize credentials from a JSON file or environment variables into a consistent schema.

scripts/extract_verification_code.py

Run this to extract likely one-time codes from email text or copied verification messages after the user authorizes that step.

平台分布

OpenClaw

78.24%
按下载量换算2,785

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

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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