菜单
Apply the OneWave design style (tokens + theme) to a frontend project. Trigger when the user asks to brand a site, apply the OneWave look, set up design tokens, theme an app, or fix off-brand colors and typography.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | apply-style |
| description | Apply the OneWave design style (tokens + theme) to a frontend project. Trigger when the user asks to brand a site, apply the OneWave look, set up design tokens, theme an app, or fix off-brand colors and typography. |
Apply a warm, earth-toned, dark-background design system as tokens and a theme
binding. Keep entry work lean; pull exact values from references/tokens.md and
stack notes from references/stacks.md.
tailwind.config.{js,ts,cjs,mjs}, a global CSS
file, and the framework in package.json. Record what you find.references/tokens.md for the canonical color, type, spacing, and radius
values. Treat that file as the source of truth.:root in the project's
global stylesheet. Group by color, typography, spacing, and radius.references/stacks.md: extend the Tailwind
theme to consume the custom properties, or map plain-CSS utility classes.Run the AI-news crew (scout, analyst, editor) to sweep the field with web search and ship a ranked briefing. Trigger when the user asks for an AI news brief, a daily or weekly AI roundup, "what shipped in AI", a model-release recap, or wants the standing cadence run.
Use when the user wants to monitor, track, or compare competitors, their pricing pages, or their published content, and report what changed since the last check. Triggers on requests like "watch competitor X", "did their pricing change", "what did they ship", or "diff competitors against last time".
Use when the user wants to turn one source piece (blog post, transcript, doc, notes, or URL) into multiple channel-ready formats — posts, a thread, an email, and a video script. Triggers on "repurpose", "atomize", "turn this into", "make social content from", or "one piece into many".
Scan official AI release notes, changelogs, and deprecation pages, then flag what affects the user's stack and recommend an action for each item. Trigger on requests like "what AI releases happened recently," "check if my models or tools are deprecated," "any changelog updates that affect my stack," or periodic release sweeps.