Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
日本語の概要は準備中です。原文の説明を表示しています。
Systematic exploratory QA testing of web applications — find bugs, capture evidence, and generate structured reports
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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, browser_close)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_close | Close the browser session |
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.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer review".
日本語の概要は準備中です。原文の説明を表示しています。
Add descriptions for new models from the HuggingFace router to chat-ui configuration. Use when new models are released on the router and need descriptions added to prod.yaml and dev.yaml. Triggers on requests like "add new model descriptions", "update models from router", "sync models", or when explicitly invoking /add-model-descriptions.
日本語の概要は準備中です。原文の説明を表示しています。
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
日本語の概要は準備中です。原文の説明を表示しています。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
日本語の概要は準備中です。原文の説明を表示しています。
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
日本語の概要は準備中です。原文の説明を表示しています。