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-imagine) unless the user has explicitly pinned a different preferred_image_backend.
   • 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-imagine), 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, image_generate, baoyu-imagine) 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#

OptionDescription--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.--yesNon-interactive: skip all confirmations, use EXTEND.md or built-in defaults, auto-confirm recommended plan (Path A)

Dimensions#

Three independent knobs combine freely:

DimensionControlsOptionsStyleVisual aesthetics (lines, decorations, rendering)12 styles (see Styles below)LayoutInformation structure (density, arrangement)8 layouts (see Layouts below)Palette (optional)Color override, replaces the style's default colorsmacaron / 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)#

StyleDescriptioncute (Default)Sweet, adorable, girly aestheticfreshClean, refreshing, naturalwarmCozy, friendly, approachableboldHigh impact, attention-grabbingminimalUltra-clean, sophisticatedretroVintage, nostalgic, trendypopVibrant, energetic, eye-catchingnotionMinimalist hand-drawn line art, intellectualchalkboardColorful chalk on black board, educationalstudy-notesRealistic handwritten photo style, blue pen + red annotations + yellow highlighterscreen-printBold poster art, halftone textures, limited colors, symbolic storytellingsketch-notesHand-drawn educational infographic, macaron pastels on warm cream, wobble lines

Per-style specifications: references/presets/<style>.md.

Layouts (8)#

LayoutDescriptionsparse (Default)1-2 points, maximum impactbalanced3-4 points, standarddense5-8 points, knowledge-card stylelistEnumeration / ranking (4-7 items)comparisonSide-by-side contrastflowProcess / timeline (3-6 steps)mindmapCenter-radial (4-8 branches)quadrantFour-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.

PaletteBackgroundZone ColorsAccentFeelmacaronWarm cream #F5F0E8Blue #A8D8EA, Lavender #D5C6E0, Mint #B5E5CF, Peach #F8D5C4Coral #E8655ASoft, educationalwarmSoft peach #FFECD2Orange #ED8936, Terracotta #C05621, Golden #F6AD55, Rose #D4A09ASienna #A0522DEarth tones, cozyneonDark purple #1A1025Cyan #00F5FF, Magenta #FF00FF, Green #39FF14, Pink #FF6EC7Yellow #FFFF00High-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:

PresetStyleLayoutBest Forknowledge-cardnotiondense干货知识卡、概念科普checklistnotionlist清单、排行榜concept-mapnotionmindmap概念图、知识脉络swotnotionquadrantSWOT 分析、四象限tutorialchalkboardflow教程步骤、操作流程classroomchalkboardbalanced课堂笔记、知识讲解study-guidestudy-notesdense学习笔记、考试重点hand-drawn-edusketch-notesflow手绘教程、流程图解sketch-cardsketch-notesdense手绘知识卡sketch-summarysketch-notesbalanced手绘总结、图文笔记

Lifestyle & Sharing:

PresetStyleLayoutBest Forcute-sharecutebalanced少女风分享、日常种草girlycutesparse甜美封面、氛围感cozy-storywarmbalanced生活故事、情感分享product-reviewfreshcomparison产品对比、测评nature-flowfreshflow健康流程、自然主题

Impact & Opinion:

PresetStyleLayoutBest Forwarningboldlist避坑指南、重要提醒versusboldcomparison正反对比clean-quoteminimalsparse金句、极简封面pro-summaryminimalbalanced专业总结、商务内容

Trend & Entertainment:

PresetStyleLayoutBest Forretro-rankingretrolist复古排行、经典盘点throwbackretrobalanced怀旧分享pop-factspoplist趣味冷知识hypepopsparse炸裂封面、惊叹分享

Poster & Editorial:

PresetStyleLayoutBest Forposterscreen-printsparse海报风封面、影评书评editorialscreen-printbalanced观点文章、文化评论cinematicscreen-printcomparison电影对比、戏剧张力

Full prompt-fragment definitions: references/style-presets.md.

Auto-Selection#

Match content signals to the best combo. First row whose keywords appear wins; fall back to cute-share if nothing matches.

Signals in sourceStyleLayoutRecommended presetbeauty, fashion, cute, girl, pinkcutesparse/balancedcute-share, girlyhealth, nature, fresh, organicfreshbalanced/flowproduct-review, nature-flowlife, story, emotion, warmwarmbalancedcozy-storywarning, important, must, criticalboldlist/comparisonwarning, versusprofessional, business, elegantminimalsparse/balancedclean-quote, pro-summaryclassic, vintage, traditionalretrobalancedthrowback, retro-rankingfun, exciting, wow, amazingpopsparse/listhype, pop-factsknowledge, concept, productivity, SaaSnotiondense/listknowledge-card, checklisteducation, tutorial, learning, classroomchalkboardbalanced/densetutorial, classroomnotes, handwritten, study guide, realisticstudy-notesdense/list/mindmapstudy-guidemovie, poster, opinion, editorial, cinematicscreen-printsparse/comparisonposter, editorial, cinematichand-drawn, infographic, workflow, 手绘, 图解sketch-notesflow/balanced/densehand-drawn-edu, sketch-card, sketch-summary

Style × Layout Matrix#

Compatibility scores (✓✓ highly recommended, ✓ works well, ✗ avoid). Use when the user picks a non-default combo and you want to flag a poor match.

sparsebalanceddenselistcomparisonflowmindmapquadrantcute✓✓✓✓✓✓✓✓✓✓✓fresh✓✓✓✓✓✓✓✓✓✓✓warm✓✓✓✓✓✓✓✓✓✓✓bold✓✓✓✓✓✓✓✓✓✓✓✓minimal✓✓✓✓✓✓✓✓✓✓✓retro✓✓✓✓✓✓✓✓✓✓✓pop✓✓✓✓✓✓✓✓✓✓✓✓notion✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓chalkboard✓✓✓✓✓✓✓✓✓✓✓✓✓✓study-notes✗✓✓✓✓✓✓✓✓✓✓screen-print✓✓✓✓✗✓✓✓✓✗✓✓sketch-notes✓✓✓✓✓✓✓✓✓✓✓✓✓

Outline Strategies#

Three differentiated approaches — each produces a structurally different outline. The workflow recommends one; Path C generates all three and lets the user choose.

StrategyConceptBest forStructureA — Story-DrivenPersonal experience as the thread, emotional resonance firstReviews, personal shares, transformationHook → Problem → Discovery → Experience → ConclusionB — Information-DenseValue-first, efficient information deliveryTutorials, comparisons, checklistsCore conclusion → Info card → Pros/Cons → RecommendationC — Visual-FirstVisual impact as core, minimal textHigh-aesthetic products, lifestyle, mood contentHero image → Detail shots → Lifestyle scene → CTA

Reference Images#

User-supplied refs are separate from the internal "image-1 as anchor" chain (Step 3) — they layer on top of it.

Intake: via --ref <files...> or paths pasted in conversation.

• File path → copy to refs/NN-ref-{slug}.{ext}
• Pasted with no path → ask for the path, or extract style traits as a text fallback

Usage modes (per reference):

UsageEffectdirectPass the file to the backend (typically on image 1 only, so the anchor propagates through the chain)styleExtract style traits and append to every card's prompt bodypaletteExtract hex colors and append to every card's prompt body

Record refs in each affected card's prompt frontmatter:

yaml

references:
  - ref_id: 01
    filename: 01-ref-brand.png
    usage: direct

At generation time: verify files exist. Image 1 with usage: direct + backend that accepts refs → pass via the backend's ref parameter (becomes the chain anchor). Images 2+ keep using image-1 as --ref per Step 3 — do NOT re-stack user refs on top (avoids conflicting signals). For style/ palette, embed extracted traits in every prompt.

File Layout#

text

image-cards/{topic-slug}/
├── source-{slug}.{ext}
├── analysis.md
├── outline-strategy-{a,b,c}.md    # Path C only
├── outline.md
├── prompts/NN-{type}-{slug}.md
├── NN-{type}-{slug}.png
└── refs/                          # only if --ref used

Slug: 2-4 words, kebab-case. "AI 工具推荐" → ai-tools-recommend. On collision, append -YYYYMMDD-HHMMSS.

Backup rule (applies throughout): before overwriting any file — source, outline, prompt, image — rename the existing one to <name>-backup-YYYYMMDD-HHMMSS.<ext>. This protects user edits.

Workflow#

text

- [ ] Step 0: Load EXTEND.md ⛔ BLOCKING (interactive only)
- [ ] Step 1: Analyze content → analysis.md
- [ ] Step 2: Smart Confirm ⚠️ REQUIRED (Path A / B / C)
- [ ] Step 3: Generate images
- [ ] Step 4: Completion report

Step 0: Load EXTEND.md ⛔ BLOCKING#

Check these paths in order; first hit wins:

PathScope.baoyu-skills/baoyu-image-cards/EXTEND.mdProject${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-image-cards/EXTEND.mdXDG$HOME/.baoyu-skills/baoyu-image-cards/EXTEND.mdUser home

• Found → read, parse, print a summary (style / layout / watermark / language), continue.
• Not found + interactive → run first-time setup (see references/config/first-time-setup.md) and save before anything else. Do NOT analyze content or ask style questions until preferences exist — this keeps first-run behavior predictable.
• Not found + --yes → skip setup, use built-in defaults (no watermark, style/layout auto-selected, language from content). Do not prompt, do not create EXTEND.md.

EXTEND.md keys: watermark, preferred style/layout, custom style definitions, language preference, preferred image backend, generation batch size. Schema: references/config/preferences-schema.md.

Step 1: Analyze Content → analysis.md#

1. Save the source (backup rule applies if source.md exists).
2. Run the deep analysis in references/workflows/analysis-framework.md: content type, hook potential, audience, engagement signals, visual opportunity map, swipe flow.
3. Detect source language, pick recommended image count (2-10).
4. Auto-recommend strategy + style + layout + palette using the Auto-Selection table above.
5. Write everything to analysis.md.

Step 2: Smart Confirm ⚠️ REQUIRED#

Hard gate: this step is mandatory per the Confirmation Policy — Step 3 cannot start until the user confirms here (or explicitly opts out with --yes / equivalent wording in the current request).

Goal: present the auto-recommended plan and let the user confirm or adjust. Skip this step entirely under --yes — proceed with Path A using the analysis and any CLI overrides.

Display summary before asking:

text

📋 内容分析
  主题：[topic] | 类型：[content_type]
  要点：[key points]
  受众：[audience]

🎨 推荐方案（自动匹配）
  策略：[A/B/C] [name]（[reason]）
  风格：[style] · 布局：[layout] · 配色：[palette or 默认] · 预设：[preset]
  图片：[N]张（封面+[N-2]内容+结尾）
  元素：[background] / [decorations] / [emphasis]

Then ask one question — three paths. Verbatim option copy: references/confirmation.md.

Path A — Quick confirm (trust auto-recommendation): generate a single outline using the recommended strategy + style → save to outline.md → Step 3.

Path B — Customize: ask five questions (strategy/style, layout, palette, count, optional notes) with the recommendation pre-filled — blanks keep the recommendation. Generate one outline with the user's choices → outline.md → Step 3. See references/confirmation.md.

Path C — Detailed mode: two sub-confirmations.

• Step 2a — Content understanding: ask selling points (multi-select), audience, style preference (authentic / professional / aesthetic / auto), optional context. Update analysis.md.
• Step 2b — Three outline variants: generate outline-strategy-a.md, outline-strategy-b.md, outline-strategy-c.md. Each MUST have a different structure AND a different recommended style — include style_reason in the frontmatter. Page-count heuristic: A ~4-6, B ~3-5, C ~3-4. Template: references/workflows/outline-template.md; frontmatter example in references/confirmation.md.
• Step 2c — Selection: ask three questions (outline A/B/C/Combined, style, visual elements). Save selected/merged outline to outline.md → Step 3.

Step 3: Generate Images#

With confirmed outline + style + layout + palette:

Visual consistency — image-1 anchor chain: character / mascot / color rendering drifts between calls unless you anchor them. Generate image 1 (cover) first WITHOUT --ref, then pass image 1 as --ref to every subsequent image. This is the single most important consistency trick for this skill — don't skip it even if the backend also supports a session ID.

Generation flow:

1. Write the full prompt for every image to prompts/NN-{type}-{slug}.md in the user's preferred language (backup rule applies), then verify all selected prompt files exist.
2. Generate image 1 first without --ref; backup rule applies to the PNG file. This establishes the anchor.
3. Build a task list for images 2+ using image 1 as --ref <path-to-image-01.png>.
4. Dispatch images 2+ in batches per the ## Batch Generation Policy: backend native batch first, runtime parallel tool calls second, sequential only as fallback.
5. Report progress after each completed image. On failure, retry only the failed item once from the same saved prompt file.

Watermark (if enabled in EXTEND.md): append to the generation prompt:

text

Include a subtle watermark "[content]" positioned at [position].
The watermark should be legible but not distracting.

See references/config/watermark-guide.md.

Backend selection: per the Image Generation Tools rule at the top — use whatever is available, ask once if multiple, before any generation. Under --yes, use the EXTEND.md preference and fall back to the first available backend. Prompt files MUST exist before invoking any backend.

Session ID (if the backend supports --sessionId): use cards-{topic-slug}-{timestamp} for every image; combined with the ref chain this gives maximum consistency.

Step 4: Completion Report#

text

Image Card Series Complete!

Topic: [topic]
Mode: [Quick / Custom / Detailed]
Strategy: [A/B/C/Combined]
Style: [name]
Palette: [name or "default"]
Layout: [name or "varies"]
Location: [directory]
Images: N total

✓ analysis.md
✓ outline.md
✓ outline-strategy-a/b/c.md (detailed mode only)

- 01-cover-[slug].png ✓ Cover (sparse)
- 02-content-[slug].png ✓ Content (balanced)
- ...
- NN-ending-[slug].png ✓ Ending (sparse)

Content Breakdown Principles#

PositionPurposeTypical layoutCover (image 1)Hook + visual impactsparseContent (middle)Core value per imagebalanced / dense / list / comparison / flowEnding (last)CTA / summarysparse or balanced

For the style × layout compatibility matrix, see the Style × Layout Matrix above.

Image Modification#

ActionHowEditUpdate prompts/NN-{type}-{slug}.md first, then regenerate with the same session IDAddSpecify position, create prompt, generate, renumber subsequent files NN+1, update outlineDeleteRemove files, renumber subsequent NN-1, update outline

Always update the prompt file before regenerating — it's the source of truth and makes changes reproducible.

Text correction policy:

• If a card's title, body copy, tags, or any other rendered text is misspelled, garbled, hard to read, or visually weak, do not patch the bitmap with code.
• For text-correction regenerations, write a new prompt file and a new output path so the flawed candidate is preserved for comparison.
• Post-processing is limited to crop, resize, compression, or format conversion that does not alter text or the main composition.

References#

FileContentreferences/confirmation.mdVerbatim AskUserQuestion copy for every confirmation pathreferences/style-presets.mdFull preset shortcut definitionsreferences/presets/<style>.mdPer-style element definitionsreferences/palettes/<name>.mdPer-palette color definitionsreferences/elements/canvas.mdAspect ratios, safe zones, grid layoutsreferences/elements/image-effects.mdCutout, stroke, filtersreferences/elements/typography.mdDecorated text, tags, text directionreferences/elements/decorations.mdEmphasis marks, backgrounds, doodles, framesreferences/workflows/analysis-framework.mdContent analysis frameworkreferences/workflows/outline-template.mdOutline template with layout guidereferences/workflows/prompt-assembly.mdPrompt assembly guidereferences/config/preferences-schema.mdEXTEND.md schemareferences/config/first-time-setup.mdFirst-time setup flowreferences/config/watermark-guide.mdWatermark configuration

Notes#

• Auto-retry once on generation failure before reporting an error.
• For sensitive public figures, use stylized cartoon alternatives.
• Smart Confirm (Step 2) is required; Detailed mode adds a second confirmation (2a + 2c).

Changing Preferences#

EXTEND.md lives at the first matching path listed in Step 0. Three ways to change it:

• Edit directly — open EXTEND.md and change fields. Full schema: references/config/preferences-schema.md.

• Reconfigure interactively — delete EXTEND.md (or ask "reconfigure baoyu-image-cards preferences" / "重新配置"). The next run re-triggers first-time setup.

• Common one-line edits:

  • preferred_image_backend: auto — default; runtime-native tool wins, falls back to the only installed backend, asks only if multiple non-native are present.
  • preferred_image_backend: codex-imagegen — pin to Codex's built-in.
  • preferred_image_backend: baoyu-imagine — pin to the baoyu-imagine skill.
  • preferred_image_backend: ask — confirm backend every run.
  • generation_batch_size: 4 — default number of images to render concurrently when the backend/runtime supports batch or parallel generation.
  • preferred_style: notion, preferred_layout: dense, preferred_palette: macaron, language: zh.
  • watermark.enabled: true + watermark.content: "@handle" — add a watermark.