Orchestrates a multi-agent loop involving planning, development, review, and publishing sub-agents to implement and publish features test-first and with high standards compliance.
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。
Manual browser testing and automation using Chrome DevTools MCP server. Handles port management, app launch, browser automation, login, and end-to-end testing.
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。
実行スコア 未検証
インストール方法を見る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 enables manual browser testing and automation using the Chrome DevTools MCP server. It orchestrates the full workflow from port management through application launch, browser automation, login, and end-to-end testing.
Check if port 3000 is free:
lsof -i :3000
If port is in use:
If port is free:
Launch the application in terminal:
Initialize Chrome DevTools MCP connection:
http://localhost:3000Execute login sequence:
Perform end-to-end tests using MCP tools:
Available MCP tool categories:
click, type_text, fill, fill_form, hover, press_key, drag, upload_file, handle_dialog, click_atnavigate_page, new_page, select_page, close_page, list_pages, wait_foremulate, resize_pageperformance_start_trace, performance_stop_trace, performance_analyze_insightlist_network_requests, get_network_requesttake_screenshot, take_snapshot, evaluate_script, list_console_messages, get_console_message, lighthouse_audit, screencast_start, screencast_stopTesting best practices:
wait_for to ensure elements are present before interactionevaluate_script for custom assertionsAfter testing completion:
Key tools for testing:
navigate_page - Navigate to URLsclick - Click on elementstype_text - Type text into inputsfill - Fill form fieldswait_for - Wait for conditionstake_screenshot - Capture screenshotslist_console_messages - Check for errorsevaluate_script - Run custom JavaScriptlighthouse_audit - Performance/accessibility auditsPort conflicts:
Application launch failures:
Browser automation failures:
Login failures:
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ログインなしで書き込めます。使ってみた感想、質問、動かなかった環境などを気軽にどうぞ。
まだコメントはありません。最初のコメントを書いてみませんか。
Orchestrates a multi-agent loop involving planning, development, review, and publishing sub-agents to implement and publish features test-first and with high standards compliance.
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。
Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch.
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。
Generates comprehensive AI context, AGENTS.md, and structured documentation in a context/ directory for any brownfield codebase using Tree-sitter AST extraction, dependency analysis, predefined python scripts, and orchestrated subagents.
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。
Breaks work into ordered tasks. Use when you have a spec or clear requirements and need to break work into implementable tasks. Use when a task feels too large to start, when you need to estimate scope, or when parallel work is possible.
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。
Progressively investigate PRs, commits, releases, and project evolution. Start with a lightweight assessment, dynamically deepen analysis based on complexity and risk, use subagents for independent investigations, and maintain evidence-backed project knowledge.
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。
Creates a new feature branch from current git changes, commits them, pushes to the remote, and opens a github pull request using the `gh` cli. Use this skill when asked to create a github pull request
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。