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argentos-dogfood
Systematic exploratory QA testing of web applications — find bugs, capture evidence, and generate structured reports
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
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Systematic exploratory QA testing of web applications — find bugs, capture evidence, and generate structured reports
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Run Codex CLI, Claude Code, OpenCode, or Pi Coding Agent via background process for programmatic control.
Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization
Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization
Production pipeline for ASCII art video — any format. Converts video/audio/images/generative input into colored ASCII character video output (MP4, GIF, image sequence). Covers: video-to-ASCII conversion, audio-reactive music visualizers, generative ASCII art animations, hybrid video+audio reactive, text/lyrics overlays, real-time terminal rendering. Use when users request: ASCII video, text art video, terminal-style video, character art animation, retro text visualization, audio visualizer in ASCII, converting video to ASCII art, matrix-style effects, or any animated ASCII output.
Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support
Manage Apple Notes via the memo CLI on macOS (create, view, search, edit).
| name | argentos-dogfood |
| description | Systematic exploratory QA testing of web applications — find bugs, capture evidence, and generate structured reports |
| version | 1.0.0 |
| metadata | {"argent":{"tags":["qa","testing","browser","web","dogfood"],"related_skills":[]},"imported_from":{"original_name":"dogfood","source":"upstream skill profile"}} |
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.
browser_navigate, browser_snapshot, browser_click, browser_type, browser_vision, browser_console, browser_scroll, browser_back, browser_press)The user provides:
./dogfood-output)Follow this 5-phase systematic workflow:
{output_dir}/
├── screenshots/ # Evidence screenshots
└── report.md # Final report (generated in Phase 5)
For each page or feature in your plan:
Navigate to the page:
browser_navigate(url="https://example.com/page")
Take a snapshot to understand the DOM structure:
browser_snapshot()
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.
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.
Test interactive elements systematically:
browser_click(ref="@eN")browser_type(ref="@eN", text="test input")browser_press(key="Tab"), browser_press(key="Enter")browser_scroll(direction="down")After each interaction, check for:
browser_console()browser_vision(question="What changed after the interaction?")For every issue found:
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.
Record the details:
Classify the issue using the issue taxonomy (see references/issue-taxonomy.md):
Generate the final report using the template at templates/dogfood-report-template.md.
The report must include:
MEDIA:<screenshot_path> for inline images)Save the report to {output_dir}/report.md.
| 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 |
browser_console() after navigating and after significant interactions. Silent JS errors are among the most valuable findings.annotate=true with browser_vision when you need to reason about interactive element positions or when the snapshot refs are unclear.MEDIA:<screenshot_path> so they can see the evidence inline.