Generates infographic image card series with 12 visual styles, 8 layouts, and 3 color palettes. Breaks content into 1-10 cartoon-style image cards optimized for social media engagement. Use when user mentions "小红书图片", "小红书种草", "小绿书", "微信图文", "微信贴图", "image cards", "图片卡片", baoyu-xhs-images, or wants

Image Card Series Generator Break down complex content into eye catching image card series with multiple style options. User Input Tools When this skill prompts the user, follow this tool selection rule (priority order): 1. Prefer built in user input tools exposed by the current agent runtime — e.g., AskUserQuestion , request user input , clarify , ask user , or any equivalent. 2. Fallback : if no such tool exists, emit a numbered plain text message and ask the user to reply with the chosen number/answer for each question. 3. Batching : if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single question, ask them one at a time in priority order. Concrete AskUserQuestion references below are examples — substitute the local equivalent in other runtimes. Image Generation Tools When this skill needs to render an image, resolve the backend in this order: 1. Current request override — if the user names a specific backend in the current message, use it. 2. Saved preference — if EXTEND.md sets preferred image backend to a backend available right now, use it. 3. Auto select (when the preference is auto , unset, or the pinned backend isn't available): Codex ( imagegen ) — first, inspect your available skills / tool inventory. If a skill named imagegen is listed, you are running inside Codex and MUST use it: invoke via the Skill tool with skill: "imagegen" , passing the saved prompt file's content (plus output path and aspect ratio per Codex imagegen 's own args). Codex imagegen is the official raster backend in that runtime and outranks any non native skill (e.g., baoyu image gen ) unless the user has explicitly pinned a different preferred image backend . Codex via codex exec ( codex imagegen ) — if the current runtime exposes no native imagegen skill but the codex CLI is on PATH with an active codex login , route through baoyu image gen provider codex cli (preferred), or — if baoyu image gen is unavailable — invoke the bundled wrapper directly. Details, parameters, and the runtime discovery procedure live in [references/codex imagegen.md](references/codex imagegen.md) — load that file only when this branch is selected. Cursor ( GenerateImage ) — if the runtime exposes a native GenerateImage tool, you are running inside Cursor and it outranks any non native skill the same way Codex imagegen does. Two hard caveats: (a) it has no aspect ratio parameter — state the target aspect ratio / dimensions explicitly in the prompt text passed as description ; (b) it does not accept an output directory — it saves to a tool managed location, so after generation copy/move the file to the skill's expected output path (e.g., outputs/.../NN xxx.png ). Reference images go in reference image paths . Other runtime native tools — if the runtime exposes a different native image tool (e.g., Hermes image generate ), use it the same way. Otherwise, if exactly one non native backend is installed (e.g., baoyu image gen ), use it. Otherwise (multiple non native backends with no runtime native tool), ask the user once — batch with any other initial questions. 4. If none are available , tell the user and ask how to proceed. ⛔ Never substitute SVG, HTML, canvas, or other code based rendering for raster image generation. Codex imagegen 's own description says it should be used "when the output should be a bitmap asset rather than repo native code or vector." If you cannot resolve a raster backend via step 3, fall through to step 4 and ask the user — do not silently emit SVG, write inline <svg markup, or produce HTML/CSS art as a substitute. This applies even if the article/section seems "diagram like": the consumer skill calling this rule has already decided that a raster image is what it needs. ⛔ Never repair rendered text by painting over a generated bitmap. Do not use ImageMagick, Pillow, Canvas, SVG, HTML/CSS, OCR scripts, or any other programmatic overlay to cover, rewrite, erase, stroke, or replace titles, body copy, tags, or any other text inside an already generated image card. If text is wrong or unclear, regenerate from a corrected prompt, switch to a layout with less on card text, or ask the user which imperfect candidate to keep. Setting preferred image backend: ask forces the step 3 prompt every run regardless of available backends. Users change the pinned backend via the Changing Preferences section below. Prompt file requirement (hard) : write each image's full, final prompt to a standalone file under prompts/ (naming: NN {type} [slug].md ) BEFORE invoking any backend. The file is the reproducibility record and lets you switch backends without regenerating prompts. Concrete tool names ( imagegen , GenerateImage , image generate , baoyu image gen ) above are examples — substitute the local equivalents under the same rule. Batch Generation Policy After every prompt file for the current generation group has been saved and verified, generate images in batches by default. Priority order: 1. Use the chosen backend's native batch / multi task interface if it exists. Each task must keep its own prompt file, output path, aspect ratio, session ID, and direct reference images. 2. If no native batch interface exists but the runtime can issue parallel tool calls, dispatch up to generation batch size images at a time. Default: 4 . An explicit user request in the current message, such as batch size 4 or "并行 4 张一起生成", overrides EXTEND.md. 3. If neither native batch nor parallel tool calls are available, generate sequentially. Rules: Honor the image 1 anchor chain: generate image 1 first, then batch images 2+ using image 1 as the reference. Never start a batch until every selected prompt file for that batch exists on disk. Retry failed items once without regenerating successful items. Do not use subagents merely to parallelize image rendering. Use subagents only for separate prompt iteration or creative exploration. Confirmation Policy Default behavior: confirm before generation . Treat explicit skill invocation, a file path, matched signals/presets, and EXTEND.md defaults as recommendation inputs only . None of them authorizes skipping confirmation. Do not start Step 3 until the user completes Step 2. Skip confirmation only when the current request explicitly says to do so, for example: yes , "直接生成", "不用确认", "跳过确认", "按默认出图", or equivalent wording. If confirmation is skipped explicitly, state the assumed strategy / style / layout / palette / count / backend in the next user facing update before generating. Language Respond in the user's language across questions, progress, errors, and completion summary. Keep technical tokens (style names, file paths, code) in English. Options Option Description style <name Visual style (see Styles below) layout <name Information layout (see Layouts below) palette <name Color override: macaron / warm / neon preset <name Style + layout + optional palette shorthand (see Presets below; per preset prompt fragments in references/style presets.md ) ref <files... Reference images applied to image 1 as the series anchor batch size <n Temporary generation batch size for this run. Default: generation batch size from EXTEND.md, otherwise 4. Clamp to 1 8. yes Non interactive: skip all confirmations, use EXTEND.md or built in defaults, auto confirm recommended plan (Path A) Dimensions Three independent knobs combine freely: Dimension Controls Options Style Visual aesthetics (lines, decorations, rendering) 12 styles (see Styles below) Layout Information structure (density, arrangement) 8 layouts (see Layouts below) Palette (optional) Color override, replaces the style's default colors macaron / warm / neon (see Palettes below) Example: style notion layout dense makes an intellectual knowledge card; add palette macaron to soften the colors without changing notion's rendering rules. A preset is a shorthand for style + layout (+ optional palette). Palette behavior : no palette → style's built in colors; palette <name → overrides colors only, rendering rules unchanged. Some styles declare a default palette (e.g., sketch notes defaults to macaron). Styles (12) Style Description cute (Default) Sweet, adorable, girly aesthetic fresh Clean, refreshing, natural warm Cozy, friendly, approachable bold High impact, attention grabbing minimal Ultra clean, sophisticated retro Vintage, nostalgic, trendy pop Vibrant, energetic, eye catching notion Minimalist hand drawn line art, intellectual chalkboard Colorful chalk on black board, educational study notes Realistic handwritten photo style, blue pen + red annotations + yellow highlighter screen print Bold poster art, halftone textures, limited colors, symbolic storytelling sketch notes Hand drawn educational infographic, macaron pastels on warm cream, wobble lines Per style specifications: references/presets/<style .md . Layouts (8) Layout Description sparse (Default) 1 2 points, maximum impact balanced 3 4 points, standard dense 5 8 points, knowledge card style list Enumeration / ranking (4 7 items) comparison Side by side contrast flow Process / timeline (3 6 steps) mindmap Center radial (4 8 branches) quadrant Four quadrant / circular sections Layout specs: references/elements/canvas.md . Palettes (optional override) Replaces the style's colors while keeping rendering rules (line treatment, textures) intact. Palette Background Zone Colors Accent Feel macaron Warm cream F5F0E8 Blue A8D8EA, Lavender D5C6E0, Mint B5E5CF, Peach F8D5C4 Coral E8655A Soft, educational warm Soft peach FFECD2 Orange ED8936, Terracotta C05621, Golden F6AD55, Rose D4A09A Sienna A0522D Earth tones, cozy neon Dark purple 1A1025 Cyan 00F5FF, Magenta FF00FF, Green 39FF14, Pink FF6EC7 Yellow FFFF00 High energy, futuristic Palette specs: references/palettes/<palette .md . Presets (style + layout shortcuts) Quick start combos, grouped by scenario. Use preset <name or recommend during Step 2. Knowledge & Learning : Preset Style Layout Best For knowledge card notion dense 干货知识卡、概念科普 checklist notion list 清单、排行榜 concept map notion mindmap 概念图、知识脉络 swot notion quadrant SWOT 分析、四象限 tutorial chalkboard flow 教程步骤、操作流程 classroom chalkboard balanced 课堂笔记、知识讲解 study guide study notes dense 学习笔记、考试重点 hand drawn edu sketch notes flow 手绘教程、流程图解 sketch card sketch notes dense 手绘知识卡 sketch summary sketch notes balanced 手绘总结、图文笔记 Lifestyle & Sharing : Preset Style Layout Best For cute share cute balanced 少女风分享、日常种草 girly cute sparse 甜美封面、氛围感 cozy story warm balanced 生活故事、情感分享 product review fresh comparison 产品对比、测评 nature flow fresh flow 健康流程、自然主题 Impact & Opinion : Preset Style Layout Best For warning bold list 避坑指南、重要提醒 versus bold comparison 正反对比 clean quote minimal sparse 金句、极简封面 pro summary minimal balanced 专业总结、商务内容 Trend & Entertainment : Preset Style Layout Best For retro ranking retro list 复古排行、经典盘点 throwback retro balanced 怀旧分享 pop facts pop list 趣味冷知识 hype pop sparse 炸裂封面、惊叹分享 Poster & Editorial : Preset Style Layout Best For poster screen print sparse 海报风封面、影评书评 editorial screen print balanced 观点文章