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.
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 when the user wants an end-to-end premium visual design workflow for any type of website or web page created directly from images.
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。
Use this skill to run an image-first design-to-code workflow for visually appealing awwward winning websites. It must adapt to the user's brief, audience, content model, interaction needs, and brand intent rather than forcing a fixed category or visual trope.
The workflow is intentionally staged:
$imagegen to create four distinct website/page design images.Load references/visual-iteration-checklist.md for design variety, implementation, close visual replication, premium website work, complex UI sections, or repeated visual refinement.
Use this skill when the user asks to:
Do not use this skill for ordinary business-logic changes, backend features, simple copy edits, or design critique that will not lead to generated images, a detailed implementation prompt, or frontend code.
The first deliverable is always four generated images. Do not jump straight to text prompts, implementation prompts, or code.
Required behavior:
$imagegen skill for phase 1.If image generation is unavailable or fails, report that blocker and ask whether the user wants text-only fallbacks. Do not silently substitute text briefs for the image stage.
Start by identifying the site context, audience, goal, style constraints, viewport, and must-have sections. If the user already gave enough context, do not pause for more input.
Generate four distinct website/page images through $imagegen. Each image must have its own visual language, not minor palette swaps. Vary structure, hierarchy, typography strategy, interaction model, information architecture, content emphasis, density, and brand behavior.
Choose directions that fit the site's purpose and audience. Different website types should develop from their own communication needs, not from a shared default template.
Use ui-mockup as the image-generation use case unless the user asks for a different raster style. The images should be polished enough for the user to choose between real visual directions, not rough wireframes.
For each direction, briefly label:
After the four images are created, stop and wait for the user to pick one or request revisions. Do not write the detailed build prompt and do not begin implementation until the user selects an image or explicitly asks to skip selection.
When the user references a selected image, verify which image they mean from the conversation context. If there is ambiguity, ask a short clarification before writing the prompt or coding.
Before coding, convert the selected image into a granular implementation prompt. The prompt should be specific enough that another frontend agent can build a near exact replica without guessing.
Include:
Inspect the project before editing. Determine the framework, routing model, styling system, package manager, existing design tokens, component patterns, image/font handling, lint/test/build commands, and primary codepath.
Respect existing architecture and design-system conventions. If the user is asking about library or framework docs, use the appropriate documentation skill before relying on memory.
If a reference image includes browser chrome, operating system UI, or mock browser decorations, treat that chrome as presentation context only. Build the actual page content, not the browser wrapper, unless the user explicitly asks for a browser mockup component.
Build the selected design as real UI code.
Requirements:
Run the page locally and capture screenshots at the reference viewport plus at least one wide desktop, one constrained desktop/tablet, and one mobile width when feasible.
Loop until the implementation has no obvious visual mismatch:
Pay special attention to failures that commonly appear in screenshot replication:
Ensure the accuracy of your final output, especially before yielding back to the user. The mock generated image and the final output should look nearly identical. Focus on the details and precision.
Run the most relevant checks available for the project: lint, typecheck, build, unit tests, and visual browser verification. If a check cannot run, state why.
Final response should include:
The output should feel like a premium website, not a generated template. Favor confident hierarchy, intentional palette, sharp spacing, precise alignment, brief-appropriate content modules, and a single strong visual thesis.
When matching a reference, optimize for visible fidelity over code cleverness. Typography, spacing, alignment, imagery, component geometry, and responsive behavior are first-class deliverables, not polish.
When the user says something looks wrong, treat it as direct visual evidence. Inspect the current implementation and reference, then patch the specific mismatch rather than explaining it away.
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
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.
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 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.
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。
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.
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 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.
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。
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.
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。
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.
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。