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.
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Manual browser testing and automation using Chrome DevTools MCP server. Handles port management, app launch, browser automation, login, and end-to-end testing.
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실행 점수 미검증
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
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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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.
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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.
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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.
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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.
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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.
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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
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