dogfood

name	dogfood
description	Exploratory QA of web apps: find bugs, evidence, reports.
version	1.0.0
platforms	["linux","macos","windows"]
metadata	{"hermes":{"tags":["qa","testing","browser","web","dogfood"],"related_skills":[]}}

Dogfood: Systematic Web Application QA Testing

Overview

This skill guides you through systematic exploratory QA testing of web applications using the browser toolset. You will navigate the application, interact with elements, capture evidence of issues, and produce a structured bug report.

Prerequisites

• Browser toolset must be available (browser_navigate, browser_snapshot, browser_click, browser_type, browser_vision, browser_console, browser_scroll, browser_back, browser_press)
• A target URL and testing scope from the user

Inputs

The user provides:

1. Target URL — the entry point for testing
2. Scope — what areas/features to focus on (or "full site" for comprehensive testing)
3. Output directory (optional) — where to save screenshots and the report (default: ./dogfood-output)

Workflow

Follow this 5-phase systematic workflow:

Phase 1: Plan

1. Create the output directory structure:

   {output_dir}/
   ├── screenshots/       # Evidence screenshots
   └── report.md          # Final report (generated in Phase 5)
   

2. Identify the testing scope based on user input.
3. Build a rough sitemap by planning which pages and features to test:
   • Landing/home page
   • Navigation links (header, footer, sidebar)
   • Key user flows (sign up, login, search, checkout, etc.)
   • Forms and interactive elements
   • Edge cases (empty states, error pages, 404s)

Phase 2: Explore

For each page or feature in your plan:

1. Navigate to the page:

   browser_navigate(url="https://example.com/page")
   

2. Take a snapshot to understand the DOM structure:

   browser_snapshot()
   

3. Check the console for JavaScript errors:

   browser_console(clear=true)
   

   Do this after every navigation and after every significant interaction. Silent JS errors are high-value findings.

4. Take an annotated screenshot to visually assess the page and identify interactive elements:

   browser_vision(question="Describe the page layout, identify any visual issues, broken elements, or accessibility concerns", annotate=true)
   

   The annotate=true flag overlays numbered [N] labels on interactive elements. Each [N] maps to ref @eN for subsequent browser commands.

5. Test interactive elements systematically:

   • Click buttons and links: browser_click(ref="@eN")
   • Fill forms: browser_type(ref="@eN", text="test input")
   • Test keyboard navigation: browser_press(key="Tab"), browser_press(key="Enter")
   • Scroll through content: browser_scroll(direction="down")
   • Test form validation with invalid inputs
   • Test empty submissions

6. After each interaction, check for:

   • Console errors: browser_console()
   • Visual changes: browser_vision(question="What changed after the interaction?")
   • Expected vs actual behavior

Phase 3: Collect Evidence

For every issue found:

1. Take a screenshot showing the issue:

   browser_vision(question="Capture and describe the issue visible on this page", annotate=false)
   

   Save the screenshot_path from the response — you will reference it in the report.

2. Record the details:

   • URL where the issue occurs
   • Steps to reproduce
   • Expected behavior
   • Actual behavior
   • Console errors (if any)
   • Screenshot path

3. Classify the issue using the issue taxonomy (see references/issue-taxonomy.md):

   • Severity: Critical / High / Medium / Low
   • Category: Functional / Visual / Accessibility / Console / UX / Content

Phase 4: Categorize

1. Review all collected issues.
2. De-duplicate — merge issues that are the same bug manifesting in different places.
3. Assign final severity and category to each issue.
4. Sort by severity (Critical first, then High, Medium, Low).
5. Count issues by severity and category for the executive summary.

Phase 5: Report

Generate the final report using the template at templates/dogfood-report-template.md.

The report must include:

1. Executive summary with total issue count, breakdown by severity, and testing scope
2. Per-issue sections with:
   • Issue number and title
   • Severity and category badges
   • URL where observed
   • Description of the issue
   • Steps to reproduce
   • Expected vs actual behavior
   • Screenshot references (use MEDIA:<screenshot_path> for inline images)
   • Console errors if relevant
3. Summary table of all issues
4. Testing notes — what was tested, what was not, any blockers

Save the report to {output_dir}/report.md.

Tools Reference

Tool	Purpose
browser_navigate	Go to a URL
browser_snapshot	Get DOM text snapshot (accessibility tree)
browser_click	Click an element by ref (@eN) or text
browser_type	Type into an input field
browser_scroll	Scroll up/down on the page
browser_back	Go back in browser history
browser_press	Press a keyboard key
browser_vision	Screenshot + AI analysis; use annotate=true for element labels
browser_console	Get JS console output and errors

Tips

• Always check browser_console() after navigating and after significant interactions. Silent JS errors are among the most valuable findings.
• Use annotate=true with browser_vision when you need to reason about interactive element positions or when the snapshot refs are unclear.
• Test with both valid and invalid inputs — form validation bugs are common.
• Scroll through long pages — content below the fold may have rendering issues.
• Test navigation flows — click through multi-step processes end-to-end.
• Check responsive behavior by noting any layout issues visible in screenshots.
• Don't forget edge cases: empty states, very long text, special characters, rapid clicking.
• When reporting screenshots to the user, include MEDIA:<screenshot_path> so they can see the evidence inline.

Terminal Demo Screenshots for PPT

When the user needs a terminal-style screenshot of an API demo for a presentation slide:

1. Prefer HTML mockup over raw terminal: Create an HTML page styled as a terminal (dark background #0d1117, macOS title bar, monospace font). This avoids emoji/font rendering issues and background process hassles.
2. Or use a self-contained bash script: Start service in background → run demo requests → print clean output → kill service. Redirect server logs to /dev/null to keep output clean.
3. Key pitfalls: UID is bash read-only (use USER_ID), WSL proxy intercepts localhost (no_proxy='*' http_proxy='' curl), Flask logs pollute output (redirect to /dev/null).