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dogfood

Exploratory QA of web apps: find bugs, evidence, reports.

Skill by AjayRajan05

IndexedMIT★ 10
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

Exploratory QA of web apps: find bugs, evidence, reports.

Use cases: testing

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What's inside

Skill name
dogfood
Description
Exploratory QA of web apps: find bugs, evidence, reports.
License
MIT
Instructions
153 lines in SKILL.md · view on GitHub

Files (3)

  • SKILL.md
  • issue-taxonomy.md · references/
  • dogfood-report-template.md · templates/

SKILL.md (first lines)

# 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

From AjayRajan05/VoiceOS, MIT.

Signals

Stars
10
Forks
4
Open issues
0
Last commit (this folder)
Jul 1, 2026 (4 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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dogfood skill. Agent Mart. https://agentmart.dev/skills/ajayrajan05-dogfood (last updated 2026-10-24)