A fast Rust-based headless browser automation CLI with Node.js fallback that enables AI agents to navigate, click, type, and snapshot pages via structured commands.
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Create comprehensive, phased implementation plans with sprints and atomic tasks. Use when user says: "make a plan", "create a plan", "plan this out", "plan the implementation", "help me plan", "design a plan", "draft a plan", "write a plan", "outline the steps", "break this down into tasks", "what's the plan for", or any similar planning request. Also triggers on explicit "/planner" or "/plan" commands.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Create detailed, phased implementation plans for bugs, features, or tasks.
Investigate the codebase:
Analyze the request:
Before doing ANY documentation search: clarify requirements with user. This will narrow and aid you in finding the right docs.
Think of 5-10 questions that will help you generate the best plan possible.
Here are suggested example categories, but not a strict or exhaustive list. You may ask anything helpful. Use best judgement & prioritize ambiguity and risk reduction:
When the plan involves any external library, API, framework, or service, use the Context7 skill to fetch the latest official docs before drafting tasks. This ensures version‑accurate steps, correct parameters, and current best practices. If no external dependencies apply, skip this phase.
Each sprint must:
Each task must be:
Bad: "Implement Google OAuth" Good:
Save the file
Generate filename from request:
-plan.md suffixExamples:
xyz-bug-plan.mdAFTER it is saved. Identify potential issues & edge cases in plan. Address proactively. Where could smth go wrong? What about the plan is ambiguous? Missing step, dependency, or pitfall?
If any gotchas found, stop & ask up to 3 more questions. (either w/ request_user_input or directly)
Refine the plan if any additional useful info is provided.
# Plan: [Task Name]
**Generated**: [Date]
**Estimated Complexity**: [Low/Medium/High]
## Overview
[Summary of task and approach]
## Prerequisites
- [Dependencies or requirements]
- [Tools, libraries, access needed]
## Sprint 1: [Name]
**Goal**: [What this accomplishes]
**Demo/Validation**:
- [How to run/demo]
- [What to verify]
### Task 1.1: [Name]
- **Location**: [File paths]
- **Description**: [What to do]
- **Dependencies**: [Previous tasks]
- **Acceptance Criteria**:
- [Specific criteria]
- **Validation**:
- [Tests or verification]
### Task 1.2: [Name]
[...]
## Sprint 2: [Name]
[...]
## Testing Strategy
- [How to test]
- [What to verify per sprint]
## Potential Risks & Gotchas
- [What could go wrong]
- [Mitigation strategies]
## Rollback Plan
- [How to undo if needed]
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A fast Rust-based headless browser automation CLI with Node.js fallback that enables AI agents to navigate, click, type, and snapshot pages via structured commands.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Create or update Codex hooks for global or project scope by asking for scope and hook type when ambiguous, then writing the hook config, scripts, and any required feature flag config.
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Build responsive, mobile-first layouts using fluid containers, flexible units, media queries, and touch-friendly design that works across all screen sizes. Use this skill when creating or modifying UI layouts, responsive grids, breakpoint styles, mobile navigation, or any interface that needs to adapt to different screen sizes. Apply when working with responsive CSS, media queries, viewport settings, flexbox/grid layouts, mobile-first styling, breakpoint definitions (mobile, tablet, desktop), touch target sizing, relative units (rem, em, %), image optimization for different screens, or testing layouts across multiple devices. Use for any task involving multi-device support, responsive design patterns, or adaptive layouts.
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Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
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Build and run Gemini 2.5 Computer Use browser-control agents with Playwright. Use when a user wants to automate web browser tasks via the Gemini Computer Use model, needs an agent loop (screenshot → function_call → action → function_response), or asks to integrate safety confirmation for risky UI actions.
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Build, transform, audit, and migrate prompts for GPT-5.6 Sol using outcome-first contracts, explicit success criteria, evidence and tool rules, approval boundaries, output requirements, and stop conditions. Use when someone asks for a GPT-5.6 prompt, wants an existing prompt optimized for GPT-5.6, or needs a prompt stack adapted from an older model.
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