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These are Open AI checking and testing agent prompts. Static Checks can be run against static artifacts such as screenshots, network logs, console logs, page text, DOMs, etc. Dynamic checks are interactive tests to be executed that are stateful and have a sequence of interactions and assertions.
Analysis of static artifacts like screenshots, logs, DOMs, and content
Security
Privacy
Usability
GenAI Code
Accessibility
Error Messages
Content Quality
Performance
WCAG
OWASP
GDPR
Search Box
AI Chatbot
Search Results
Product Details
News Content
Shopping Cart
Social Profiles
Checkout
Social Feed
Homepage
Contact Page
Pricing Page
About Page
Video Player
Legal Policies
Careers
Forms
Booking
Cookie Consent
Interactive tests with stateful sequences and assertions - similar to traditional test cases with test steps and assertions
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Static Agents
Dynamic Agents
Webpages Tested
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Static checks analyze static artifacts like screenshots, logs, DOMs, and content.
Dynamic checks are interactive tests with sequences of actions and assertions.
Join thousands of developers who are already shipping better software with AI-powered testing.
AI-powered bug reports with unprecedented context and actionable insights
Traditional bug reports are often incomplete, lacking context, and require significant investigation. Open AI-Generated bug reports provide comprehensive analysis with actionable solutions.
Include as much relevant context as possible - console logs, network calls, page elements, and user interactions.
Provide an AI-prompt that can be used to fix the issue, making it easy for developers to understand and implement solutions.
Argue for and against why this is a bug, providing comprehensive reasoning from multiple perspectives.
Provide initial assessment of issue severity with clear reasoning and priority recommendations.
Issues are stateful with human ratings, comments, and expert review capabilities for collaborative improvement.
Automatically suggest which type of engineer should handle each issue for optimal resolution.
{
"bug_title": "string", // Issue title/description
"bug_description": "string", // Detailed description
"bug_confidence": number, // Confidence level (typically 1-10)
"bug_priority": number, // Priority level (typically 1-10)
"bug_type": "string", // Issue category/type
"bug_severity": "high|medium|low",
"category": "string", // Coverage category
// Fix prompt - this is the key field you mentioned
"prompt_to_fix_this_issue": "string", // AI-generated prompt for fixing the issue
// Additional fix-related fields
"suggested_fix": "string", // Suggested solution approach
"bug_why_fix": "string", // Why fixing this issue matters
// Alternative field names (depending on context)
"prompt_to_fix_issue": "string", // Alternative field name
// UI state properties (when exported)
"trash": boolean, // User marked as trash
"star": boolean, // User starred
"comment": "string", // User comment
// Additional metadata
"tester": "string", // AI persona who found the issue (e.g., "Alejandro", "Mia")
"byline": "string", // Tester role description
"image_url": "string", // Tester avatar
"what_type_of_engineer_to_route_issue_to": "string", // Target engineer role
// Context data
"possibly_relevant_page_console_text": "string",
"possibly_relevant_network_call": "string",
"possibly_relevant_page_text": "string",
"possibly_relevant_page_elements": "string"
}
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