Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.
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。
Explore radically different module shapes before committing to one. Use when choosing an API surface, deciding what a module hides vs exposes, or when the user says 'design it twice'.
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。
Apply Ousterhout's "Design It Twice": generate 3+ radically different module shapes, compare on depth, and synthesize. The goal is deep modules — small interfaces hiding significant complexity. Do not implement; this is purely about the shape of the seam.
Use ln-design as the deepening pathway from ln-review: when review surfaces a shallow module or weak seam, explore alternative deepened module shapes here before routing to ln-scope or ln-refactor.
The module or API boundary: $ARGUMENTS
Understand the problem, the callers, the key operations, constraints, and — crucially — what complexity should be hidden inside vs exposed. If this design follows an ln-review deepening candidate, start from that candidate's files, problem, possible direction, and benefits. Skip steps you already know the answer to.
Read memory/SPEC.md first when it exists. Use its lexicon for domain terms and respect its live assumptions, decisions, and invariants. Read memory/PLAN.md when the seam touches active or near-horizon work.
Spawn 3+ sub-agents simultaneously. Each must produce a radically different shape — enforce this by assigning divergent constraints:
Each agent returns: interface (types, methods, params, invariants, ordering constraints, error modes, required configuration, and performance characteristics), usage example, what it hides, seam / adapter strategy where relevant, and trade-offs.
Show each design sequentially, then compare in prose on:
Highlight where designs diverge most.
The best design often combines insights from multiple options. Ask which shape best fits the primary use case and whether elements from other designs are worth incorporating.
Present the recommended module shape with rationale. If memory/SPEC.md exists, ensure names align with its lexicon.
Do not invent a standalone design document unless the user explicitly asks for one. Durable design choices reconcile back into memory/SPEC.md and memory/PLAN.md.
After choosing a design, present these options to the user (use tool-ask-question):
| # | Label | Target | Why |
|---|---|---|---|
| 1 | Scope a slice | ln-scope | Design is chosen, define the first slice |
| 2 | Write a spec | ln-spec | Module needs a full spec before slicing |
| 3 | Grill it more | ln-grill | Design choice raised new questions |
Recommended: 1
Adapted from mattpocock/skills/design-an-interface.
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
Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.
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。
Search the live web via Perplexity Search API. Use when you need current documentation, release notes, vendor pages, news, domain-constrained web search, or date/recency filtering. Not for local codebase search or stable docs already in context.
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。
Chrome DevTools CLI for browser automation via shell commands. Use when interacting with web pages from the command line — navigating, clicking, filling forms, inspecting console/network, taking screenshots, or extracting page content. Triggers on: browse a page, automate Chrome, inspect console, check network requests, take a screenshot, fill a form, click a button.
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。
Uses the chrome-devtools-axi CLI for browser automation, accessibility-tree snapshots, console and network inspection, screenshots, Lighthouse audits, and performance traces. Use when interacting with Chrome from the shell, especially when the user mentions chrome-devtools-axi, AX snapshots, browser debugging, or DevTools automation from the command line.
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。
Deep expertise in cmux — the terminal multiplexer with native browser views. Use when managing panes, reading terminal output, sending keystrokes, opening browser views, or manually testing web UIs and TUIs inside cmux. Triggers on: cmux, open a browser pane, split terminal, read screen, send keys, test this UI in cmux, preview in cmux.
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。
Uses the gh-axi CLI for GitHub shell operations: issue, pull request, workflow run, release, repo, search, and API tasks. Prefer this over regular `gh` for GitHub reads and simple mutations when an agent needs compact, structured, suggestion-rich output. Triggers on: gh, GitHub CLI, github issue, github pr, pull request, workflow run, github release, gh api, repo inspection, list PRs, view issue, check workflow runs, inspect repo, GitHub shell operations.
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。