Guide exploratory QA testing of web applications and generate evidence-based reports.
npx skills add https://github.com/ruiyangruiyi/hermes-agent --skill dogfood-ruiyangruiyi
Please help me install this Agent Skill. Skill: dogfood Source: https://github.com/ruiyangruiyi/hermes-agent/tree/main/skills/dogfood Command: npx skills add https://github.com/ruiyangruiyi/hermes-agent --skill dogfood-ruiyangruiyi
It helps you discover functional, visual, accessibility, UX, and console issues in a web app faster by running a repeatable exploratory QA process that produces evidence-based reports.
Run dogfood against a target URL by specifying your testing scope (e.g., full site) and an output directory so the Skill navigates, collects evidence, and writes report.md with categorized issues.
High-intent search queries and answers about installing and using this skill.
Exploratory testing for web applications with evidence screenshots involves navigating pages, capturing visual proof of suspected issues, and recording expected versus actual behavior. This process systematically uncovers functional, visual, accessibility, and console errors across a defined scope.
The best way to classify and report web QA defects is using a taxonomy-based system. Findings are categorized by severity (Critical, High, Medium, Low) and type (Functional, Visual, Accessibility, Console, UX, Content), then compiled into a structured report.
Checking for console errors and UX issues during web UI testing requires systematically navigating user flows and forms while monitoring browser console diagnostics. Capturing snapshots and screenshots provides evidence for each suspected functional or visual defect.
Yes, a browser toolset is required to perform systematic bug reporting and issue taxonomy. The testing process depends on browser automation to navigate target URLs, execute testing scope plans, capture evidence screenshots, and extract console diagnostics.
To generate a structured report for edge cases and visual defects, compile your testing evidence into an output directory. The resulting markdown report categorizes issues by severity and type, detailing steps, expected behavior, and actual results.
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