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Baoyu Image Cards

by Jim Liu 宝玉 · GitHub ↗ · v1.103.2 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install baoyu-image-cards
Description
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...
README (SKILL.md)

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):
    • If the current runtime exposes a native image tool (e.g., Codex imagegen, Hermes image_generate), use it. Runtime-native tools are preferred by default — agents that know their own tool inventory should surface the native one here.
    • 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.

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.

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 \x3Cname> Visual style (see Styles below)
--layout \x3Cname> Information layout (see Layouts below)
--palette \x3Cname> Color override: macaron / warm / neon
--preset \x3Cname> Style + layout + optional palette shorthand (see Presets below; per-preset prompt fragments in references/style-presets.md)
--ref \x3Cfiles...> Reference images applied to image 1 as the series anchor
--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 \x3Cname> → 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/\x3Cstyle>.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/\x3Cpalette>.md.

Presets (style + layout shortcuts)

Quick-start combos, grouped by scenario. Use --preset \x3Cname> 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、文化评论
cinematic screen-print comparison 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 source Style Layout Recommended preset
beauty, fashion, cute, girl, pink cute sparse/balanced cute-share, girly
health, nature, fresh, organic fresh balanced/flow product-review, nature-flow
life, story, emotion, warm warm balanced cozy-story
warning, important, must, critical bold list/comparison warning, versus
professional, business, elegant minimal sparse/balanced clean-quote, pro-summary
classic, vintage, traditional retro balanced throwback, retro-ranking
fun, exciting, wow, amazing pop sparse/list hype, pop-facts
knowledge, concept, productivity, SaaS notion dense/list knowledge-card, checklist
education, tutorial, learning, classroom chalkboard balanced/dense tutorial, classroom
notes, handwritten, study guide, realistic study-notes dense/list/mindmap study-guide
movie, poster, opinion, editorial, cinematic screen-print sparse/comparison poster, editorial, cinematic
hand-drawn, infographic, workflow, 手绘, 图解 sketch-notes flow/balanced/dense hand-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.

sparse balanced dense list comparison flow mindmap quadrant
cute ✓✓ ✓✓ ✓✓
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.

Strategy Concept Best for Structure
A — Story-Driven Personal experience as the thread, emotional resonance first Reviews, personal shares, transformation Hook → Problem → Discovery → Experience → Conclusion
B — Information-Dense Value-first, efficient information delivery Tutorials, comparisons, checklists Core conclusion → Info card → Pros/Cons → Recommendation
C — Visual-First Visual impact as core, minimal text High-aesthetic products, lifestyle, mood content Hero 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 \x3Cfiles...> 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):

Usage Effect
direct Pass the file to the backend (typically on image 1 only, so the anchor propagates through the chain)
style Extract style traits and append to every card's prompt body
palette Extract hex colors and append to every card's prompt body

Record refs in each affected card's prompt frontmatter:

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

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 \x3Cname>-backup-YYYYMMDD-HHMMSS.\x3Cext>. This protects user edits.

Workflow

- [ ] 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:

Path Scope
.baoyu-skills/baoyu-image-cards/EXTEND.md Project
${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-image-cards/EXTEND.md XDG
$HOME/.baoyu-skills/baoyu-image-cards/EXTEND.md User 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. 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:

📋 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.

For each image (cover, content, ending):

  1. Write the full prompt to prompts/NN-{type}-{slug}.md in the user's preferred language (backup rule applies).
  2. Generate:
    • Image 1: no --ref (establishes the anchor).
    • Images 2+: add --ref \x3Cpath-to-image-01.png>.
    • Backup rule applies to the PNG files.
  3. Report progress after each image.

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

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

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

Position Purpose Typical layout
Cover (image 1) Hook + visual impact sparse
Content (middle) Core value per image balanced / dense / list / comparison / flow
Ending (last) CTA / summary sparse or balanced

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

Image Modification

Action How
Edit Update prompts/NN-{type}-{slug}.md first, then regenerate with the same session ID
Add Specify position, create prompt, generate, renumber subsequent files NN+1, update outline
Delete Remove files, renumber subsequent NN-1, update outline

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

References

File Content
references/confirmation.md Verbatim AskUserQuestion copy for every confirmation path
references/style-presets.md Full preset shortcut definitions
references/presets/\x3Cstyle>.md Per-style element definitions
references/palettes/\x3Cname>.md Per-palette color definitions
references/elements/canvas.md Aspect ratios, safe zones, grid layouts
references/elements/image-effects.md Cutout, stroke, filters
references/elements/typography.md Decorated text, tags, text direction
references/elements/decorations.md Emphasis marks, backgrounds, doodles, frames
references/workflows/analysis-framework.md Content analysis framework
references/workflows/outline-template.md Outline template with layout guide
references/workflows/prompt-assembly.md Prompt assembly guide
references/config/preferences-schema.md EXTEND.md schema
references/config/first-time-setup.md First-time setup flow
references/config/watermark-guide.md Watermark 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.
    • preferred_style: notion, preferred_layout: dense, preferred_palette: macaron, language: zh.
    • watermark.enabled: true + watermark.content: "@handle" — add a watermark.
Usage Guidance
What to consider before installing: - The skill is instruction-only and does not download code or ask for API keys, which reduces remote-execution risk. However, it will create and persist files on disk: an EXTEND.md preference file (either in the project at .baoyu-skills/baoyu-xhs-images/ or in the user's home at ~/.baoyu-skills/baoyu-xhs-images/) and per-image prompt files under a prompts/ folder. Decide whether you are comfortable with the skill writing configuration and prompt content to those locations. - The SKILL.md enforces a blocking first-time setup flow that must complete before other operations; this means the agent will prompt to save preferences and then immediately write files. If you want to review what it would write first, avoid auto-confirm flags like --yes and answer setup prompts cautiously. - Prompts saved to disk may contain sensitive or private data (e.g., proprietary copy, user-supplied details). If that is a concern, run the skill in a sandboxed workspace or inspect the written files after setup and before generating images, or modify the save location to a project-limited directory rather than your home directory. - The metadata does not declare these config paths or filesystem actions; that mismatch could be an oversight but reduces transparency. Ask the skill author (or check the repository) whether you can opt out of persistent saving or change the default save location. - If you need stronger assurance, request that the skill be updated to: (1) explicitly declare required config paths in metadata, (2) make the initial setup optional (not blocking), and (3) prompt for explicit write permission with the exact paths before creating files. These changes would raise confidence in the skill's behavior.
Capability Analysis
Type: OpenClaw Skill Name: baoyu-image-cards Version: 1.103.2 The baoyu-image-cards skill bundle is a well-structured tool designed to generate social media infographic series. It includes comprehensive workflows for content analysis, visual style selection (12 styles, 8 layouts), and multi-image generation with visual consistency anchors. The instructions in SKILL.md prioritize user control through a mandatory confirmation policy and include safety features like automatic file backups to prevent data loss. No evidence of malicious intent, data exfiltration, or unauthorized system access was found; the logic is entirely consistent with its stated purpose of creating image cards for platforms like Xiaohongshu.
Capability Assessment
Purpose & Capability
The described purpose (generate image card series) aligns with the instructions (styles, palettes, image backend selection). However, the skill metadata declares no required config paths or environment variables, while the SKILL.md and references explicitly require creating and persisting an EXTEND.md in .baoyu-skills/ or ~/.baoyu-skills/ and writing prompt files under prompts/. That discrepancy between declared requirements and actual file writes is notable.
Instruction Scope
Runtime instructions mandate a blocking first-time setup (must complete before any other steps), require creating EXTEND.md saved to project or user home, and require writing each image prompt to prompts/ before invoking any image backend. These steps cause persistent writes of user content and preferences and could store potentially sensitive prompt/user-provided content. There are no instructions to sanitize or prompt for explicit filesystem permission beyond the setup flow; the skill does not contact external endpoints or request secrets.
Install Mechanism
No install spec and no code files — instruction-only skill. This minimizes supply-chain risk because nothing is downloaded or executed locally beyond the agent following the SKILL.md prose.
Credentials
The skill requests no environment variables or credentials (consistent with no external APIs). Still, it expects to read/write preference/config files in project or home directories and to create prompt files; these filesystem actions are not declared in the metadata (no required config paths listed), an inconsistency that reduces transparency about what the skill will access.
Persistence & Privilege
Although not marked always:true, the skill requests persistent presence via writing EXTEND.md (user or project scope) and storing prompts and outline files. The mandatory blocking setup that must complete before other steps increases the chance of unwanted persistent changes. The skill does not request other skills' configs, but it will create and reuse files in the user's filesystem.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install baoyu-image-cards
  3. After installation, invoke the skill by name or use /baoyu-image-cards
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.103.2
- Improved user input handling: now prefers built-in agent tools for prompting users, with a fallback to numbered plain text if needed. - Image backend selection logic clarified and made explicit, including override, preference, and auto-select order. - Added requirement to emit the final image prompt file before invoking any backend. - Confirmation policy updated: always confirm before generation unless explicitly told not to; now lists clear skip rules. - Added references to new confirmation logic and updated workflow instructions. - Minor documentation improvements and more precise descriptions throughout.
v1.103.1
## 1.103.1 - 2026-04-13 ### Fixes - `baoyu-markdown-to-html`: decode HTML entities and strip tags from article summary - `baoyu-post-to-weibo`: decode HTML entities and strip tags from article summary
v1.103.0
## 1.103.0 - 2026-04-12 ### Features - baoyu-diagram: add multi-diagram mode for article-wide diagram generation ### Fixes - baoyu-article-illustrator: prevent color names and hex codes from appearing as visible text in generated images - baoyu-cover-image: prevent color names and hex codes from appearing as visible text in generated images - baoyu-image-cards: prevent color names from appearing as visible text in generated images - baoyu-post-to-wechat: decode HTML entities and strip tags from article summary
v1.0.0
- Initial release of baoyu-image-cards. - Generates infographic image card series with 11 visual styles and 8 layouts. - Breaks content into 1–10 cartoon-style cards optimized for social media platforms. - Supports style/layout auto-selection, manual flags, and preset shortcuts. - Designed for both interactive use and scheduled/automated tasks. - Ideal when users mention relevant social media or infographic keywords.
Metadata
Slug baoyu-image-cards
Version 1.103.2
License MIT-0
All-time Installs 1
Active Installs 1
Total Versions 4
Frequently Asked Questions

What is Baoyu Image Cards?

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... It is an AI Agent Skill for Claude Code / OpenClaw, with 283 downloads so far.

How do I install Baoyu Image Cards?

Run "/install baoyu-image-cards" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Baoyu Image Cards free?

Yes, Baoyu Image Cards is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Baoyu Image Cards support?

Baoyu Image Cards is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Baoyu Image Cards?

It is built and maintained by Jim Liu 宝玉 (@jimliu); the current version is v1.103.2.

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