Create a professional, eye-catching blog post header image sized for web (1200×628) with optional title composition guidance.
npx skills add https://github.com/SamurAIGPT/Generative-Media-Skills --skill muapi-blog-header
Create a professional, eye-catching blog post header image sized for web (1200×628) with optional title composition guidance.
| Name | Type | Required | Default | Description |
|:---|:---|:---|:---|:---|
| topic | text | yes | — | The blog post topic or title (e.g. "10 productivity hacks for remote developers"). |
| publication_style | text | no | clean, editorial, modern, professional | Visual style matching the blog's brand (e.g. "dark tech blog", "warm lifestyle", "minimalist corporate"). |
| dominant_color | text | no | — | Optional primary color direction (e.g. "deep blue", "warm amber", "monochrome"). |
Generate a single, publication-quality blog header in one shot — no plan needed unless the user requests variants.
{{topic}}:{{publication_style}}, editorial photography, 16:9 wide, professional blog header, ample negative space on the left side for title text overlay, {{dominant_color}} color palette.
muapi image generate (model=gpt-image-2-text-to-image, aspect_ratio=21:9).Return:
muapi image edit to adapt it instead of generating from scratch.blog header, blog image, article image, featured image, og image, open graph image, hero image
muapi CLI commands. Use muapi auth configure first if MUAPI_API_KEY is unset.curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}' and poll with muapi predict wait <request_id>.{{input_name}} placeholders with the user's actual inputs before issuing each call.Extract cognitive patterns and thinking fingerprints from any text. Use this skill when the user wants to analyze how someone thinks, understand cognitive style, profile writing or speech patterns, compare thinking styles between people, asks "what's my thinking style", "analyze how this person reasons", "cognitive profile", "thinking pattern", "DHDNA", "digital DNA", or wants to understand the mind behind any text. Also trigger when the user provides text and wants deeper insight into the author's reasoning patterns, decision-making style, or cognitive signature.
GSAP animation reference for HyperFrames. Covers gsap.to(), from(), fromTo(), easing, stagger, defaults, timelines (gsap.timeline(), position parameter, labels, nesting, playback), and performance (transforms, will-change, quickTo). Use when writing GSAP animations in HyperFrames compositions.
配图助手 - 把文章/模块内容转成统一风格、少字高可读的 16:9 信息图提示词;先定“需要几张图+每张讲什么”,再压缩文案与隐喻,最后输出可直接复制的生图提示词并迭代。
| YouTube clip generation and editing with automated workflows — pull source video, slice highlights, add captions, and export.
Best practices for writing Remotion animations that stay intuitive for agents and editable in Remotion Studio Visual Mode.
YouTube transcript extraction and content reformatting: given a YouTube video URL, opens the video's transcript panel, extracts all timestamped segments, and transforms the raw transcript into summaries, chapter outlines, Twitter/X threads, blog posts, or notable quotes. Use when the user shares a YouTube URL or video link, asks to summarize a video, get a transcript, extract content from a YouTube video, get YouTube captions, extract YouTube captions, download YouTube captions, transcribe YouTube video, YouTube video to text, make a thread from YouTube, YouTube to blog post, YouTube to article, pull transcript from YouTube, YouTube content extraction, convert YouTube to text, video to transcript. Also applies when user wants to reformat any YouTube video content into structured output (chapters, threads, blog articles, key quotes).
跨境电商全链路自动化工具。集成1688采集、智能清洗、多平台上架(微信小店/Shopify/TikTok)、推广方案(关键词/竞品分析/广告文案)、短视频创作(MoviePy竖屏视频)、一键代发、爆品挖掘(趋势聚合+6维评分)、闲鱼二手选品捡漏(品牌识别/虚标过滤/捡漏评分/价格监控)、全自动流水线(挖掘→采集→清洗→上架→推广→视频)。
生成历史名人现代访谈短视频文案,通过古今反差与网络热梗的爆笑结合,创作具有传播力的虚构趣味内容
Take samuraigpt/muapi-blog-header from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.