AI means prompts and skills are interesting--not code.
Open source AI testing agents and skills that find bugs, generate user feedback, and create test cases
The future of browser automation for AI agents and developers
AI-first 'Selenium 5' being built by the same person that created Selenium. Even being vibe coded using Claude.
⚠️ Note: Ready for experimentation but not yet ready with backwards compatibility or Selenium parity in functionality
Analysis of static artifacts like screenshots, logs, DOMs, and content
testers.ai makes it as easy as a single click to run open and your own custom test agents against your website
Copy prompt text from any testing agent below and paste into your AI chatbot, then attach the respective artifacts (screenshots, logs, network activity, DOM, etc.)
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.
Automatically determine issue priority based on impact, frequency, and user experience considerations with detailed reasoning.
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.
Each bug object in the new OpenTest.AI format output contains the following comprehensive information:
| Field | Type | Description |
|---|---|---|
| bug_title | string | Short, descriptive title of the bug |
| bug_type | array | Categories (e.g. "usability", "WCAG", "security") |
| bug_confidence | integer | 1–10 score reflecting confidence it's a real bug |
| bug_priority | integer | 1–10 score indicating impact/severity |
| bug_reasoning_why_a_bug | string | Explanation of why this is considered a bug |
| bug_reasoning_why_not_a_bug | string | Counterargument, acknowledging uncertainty |
| suggested_fix | string | Recommended fix or mitigation strategy |
| bug_why_fix | string | Justification for why this should be fixed |
| what_type_of_engineer_to_route_issue_to | string | Suggested role (e.g. "Frontend Engineer") |
| possibly_relevant_page_console_text | string/null | Captured browser console text (if relevant) |
| possibly_relevant_network_call | string/null | Relevant network request URL |
| possibly_relevant_page_text | string/null | Snippet of page text related to the bug |
| possibly_relevant_page_elements | string/null | DOM element info (e.g. tag, href, id) |
| tester | string | Name of the human/AI tester who found it |
| byline | string | Title or role of the tester |
| image_url | string | (Optional) Image avatar of the tester |
{
"bug_title": "string",
"bug_type": "array",
"bug_confidence": "integer",
"bug_priority": "integer",
"bug_reasoning_why_a_bug": "string",
"bug_reasoning_why_not_a_bug": "string",
"suggested_fix": "string",
"bug_why_fix": "string",
"what_type_of_engineer_to_route_issue_to": "string",
"possibly_relevant_page_console_text": "string|null",
"possibly_relevant_network_call": "string|null",
"possibly_relevant_page_text": "string|null",
"possibly_relevant_page_elements": "string|null",
"tester": "string",
"byline": "string",
"image_url": "string"
}
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Static prompts analyze static artifacts like screenshots, logs, DOMs, and content.
Dynamic prompts are interactive tests with sequences of actions and assertions.
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