A secure assistant for AI agents to detect authentication barriers, fill credentials, and manage verification codes with user-approved workflows.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install auto-login-assistant
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install auto-login-assistant using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Auto Login Assistant?
The Auto Login Assistant is a specialized tool designed to help AI agents navigate authentication barriers like login screens, expired sessions, and verification-code challenges. Instead of stalling when a login wall is encountered, this skill provides a conservative and secure workflow to collect user-approved credentials and proceed with the task. It is a core component of the Openclaw Skills library, prioritizing security by refusing to bypass anti-bot systems or guess secrets, ensuring all automation remains within user-defined boundaries.
By normalizing credentials from various sources—including direct conversation, local files, and environment variables—the skill allows agents to interact with SaaS products, admin consoles, and mailboxes seamlessly. It bridges the gap between automated browsing and restricted content, providing a professional solution for session management and one-time password (OTP) handling.
Auto Login Assistant Use Cases
- Automatically identifying redirects to sign-in or session-expired pages during web navigation.
- Assisting agents in accessing protected dashboards, settings, or private mailboxes.
- Streamlining the retrieval and entry of verification codes from authorized email sources.
- Guided sign-in for administrative tasks where manual step-by-step help is inefficient.
How Auto Login Assistant Works
- Verifies the presence of a login barrier by scanning for URL patterns like auth or signin and identifying password or OTP fields.
- Requests credential sources from the user, prioritizing current conversation input, local file paths, or environment variables.
- Normalizes the collected data using specific scripts to map fields such as username, email, and password to the website's form.
- Fills the login form conservatively via the visible UI, masking secrets in all logs and explanations to maintain privacy.
- Handles verification challenges by either prompting the user for a code or extracting it from an authorized mailbox using extraction scripts.
- Confirms login success by checking for post-authentication markers like account menus, avatars, or successful navigation to the target feature.
Auto Login Assistant Setup
To deploy this within your environment, ensure the helper scripts are accessible to your agent. This skill is part of the broader Openclaw Skills ecosystem and relies on Python for credential normalization.
# Prepare the credential normalization script
python scripts/read_credentials.py --path your_config.json
# If verification code extraction is required from a text source
python scripts/extract_verification_code.py --input "your_email_body_text"
Auto Login Assistant Data Schema & Taxonomy
The skill utilizes a normalized data structure to handle credentials securely. The following fields are supported and processed via the normalization scripts:
| Field | Description |
|---|---|
| site | The target domain for the login |
| login_url | The specific URL of the authentication page |
| username / email | The primary identifier for account access |
| password | The secret key (treated as ephemeral and masked) |
| otp_email | The email address authorized for OTP retrieval |
| otp_mode | The logic used to process verification codes |
| notes | Additional context or instructions for the specific login |
Auto Login Assistant Advanced Features
- Multi-source credential resolution supporting environment variables and local JSON configurations.
- Intelligent OTP extraction that parses verification codes from authorized email content.
- Conservative form-filling logic that respects site-specific UI patterns over direct POST requests.
- Automated success validation using DOM analysis to confirm session establishment.
- Safety-first design that hands control back to the user for Captchas, QR codes, or biometric prompts.
SKILL.md
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