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argentos-dogfood
Systematic exploratory QA testing of web applications — find bugs, capture evidence, and generate structured reports
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Systematic exploratory QA testing of web applications — find bugs, capture evidence, and generate structured reports
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
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.