Data Viz Renderer
zebbern/claude-code-guide
Generate self-contained HTML/SVG infographics from JSON data, including stat cards, bar charts, flow diagrams, and mixed dashboards.
Generates infographic image card series with 12 visual styles, 8 layouts, and 3 color palettes.
$ npx skills add guanyang/open-agent-hub --skill baoyu-image-cards -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install guanyang/open-agent-hub baoyu-image-cards --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/guanyang/open-agent-hub.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/baoyu-image-cards .claude/skills/baoyu-image-cards && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "baoyu-image-cards" agent skill from https://github.com/guanyang/open-agent-hub/tree/main/skills/baoyu-image-cards into .claude/skills/baoyu-image-cards/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "baoyu-image-cards", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/guanyang/open-agent-hub/tree/main/skills/baoyu-image-cardsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add guanyang/open-agent-hub --skill baoyu-image-cards -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install guanyang/open-agent-hub baoyu-image-cards --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/guanyang/open-agent-hub.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/baoyu-image-cards .agents/skills/baoyu-image-cards && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "baoyu-image-cards" agent skill from https://github.com/guanyang/open-agent-hub/tree/main/skills/baoyu-image-cards into .agents/skills/baoyu-image-cards/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "baoyu-image-cards", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add guanyang/open-agent-hub --skill baoyu-image-cards -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install guanyang/open-agent-hub baoyu-image-cards --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/guanyang/open-agent-hub.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/baoyu-image-cards .cursor/skills/baoyu-image-cards && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "baoyu-image-cards" agent skill from https://github.com/guanyang/open-agent-hub/tree/main/skills/baoyu-image-cards into .cursor/skills/baoyu-image-cards/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "baoyu-image-cards", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/guanyang/open-agent-hub.git --path skills/baoyu-image-cards--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add guanyang/open-agent-hub --skill baoyu-image-cards -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install guanyang/open-agent-hub baoyu-image-cards --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/guanyang/open-agent-hub.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/baoyu-image-cards .gemini/skills/baoyu-image-cards && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "baoyu-image-cards" agent skill from https://github.com/guanyang/open-agent-hub/tree/main/skills/baoyu-image-cards into .gemini/skills/baoyu-image-cards/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "baoyu-image-cards", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install guanyang/open-agent-hub baoyu-image-cardsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add guanyang/open-agent-hub --skill baoyu-image-cards -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/guanyang/open-agent-hub.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/baoyu-image-cards .github/skills/baoyu-image-cards && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "baoyu-image-cards" agent skill from https://github.com/guanyang/open-agent-hub/tree/main/skills/baoyu-image-cards into .github/skills/baoyu-image-cards/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "baoyu-image-cards", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add guanyang/open-agent-hub --skill baoyu-image-cards -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install guanyang/open-agent-hub baoyu-image-cards --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/guanyang/open-agent-hub.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/baoyu-image-cards .opencode/skills/baoyu-image-cards && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "baoyu-image-cards" agent skill from https://github.com/guanyang/open-agent-hub/tree/main/skills/baoyu-image-cards into .opencode/skills/baoyu-image-cards/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "baoyu-image-cards", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
baoyu-image-cardsGenerates infographic image card series with 12 visual styles, 8 layouts, and 3 color palettes.
Baoyu Image Cards is an agent skill from guanyang/open-agent-hub. 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", or wants social media infographic series.
Its SKILL.md is about 6.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 33 other files, including reference files (for example `references/config/first-time-setup.md`, `references/config/preferences-schema.md` and `references/config/watermark-guide.md`).
It sits in Media & Creative, covering Infographics, Theming and dark mode and Image generation. The repository describes itself as: A lightweight, zero-dependency CLI tool to manage and activate capabilities for AI coding assistants (such as Claude Code, Cursor, Trae, etc.). The licence is MIT.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit acd7c6c. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Baoyu Image Cards loads about 6.7k tokens when it runs, and up to ~27k if it reads all its reference files. Until then it costs about 83 tokens; SKILL.md has 2,850 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from guanyang/open-agent-hub at commit acd7c6c, republished under its MIT licence (© guanyang). 2,850 words, ~6,696 tokens.
.claude/skills/baoyu-image-cards/SKILL.md (or your agent's skills folder). This skill also uses 28 other files; get the full folder from GitHub.Break down complex content into eye-catching image card series with multiple style options.
When this skill prompts the user, follow this tool-selection rule (priority order):
AskUserQuestion, request_user_input, clarify, ask_user, or any equivalent.Concrete AskUserQuestion references below are examples — substitute the local equivalent in other runtimes.
When this skill needs to render an image, resolve the backend in this order:
EXTEND.md sets preferred_image_backend to a backend available right now, use it.auto, unset, or the pinned backend isn't available):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.image_generate), use it the same way.baoyu-imagine), use it.⛔ 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.
After every prompt file for the current generation group has been saved and verified, generate images in batches by default.
Priority order:
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.Rules:
Default behavior: confirm before generation.
EXTEND.md defaults as recommendation inputs only. None of them authorizes skipping confirmation.--yes, "直接生成", "不用确认", "跳过确认", "按默认出图", or equivalent wording.Respond in the user's language across questions, progress, errors, and completion summary. Keep technical tokens (style names, file paths, code) in English.
| 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) |
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).
| 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.
| 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.
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.
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、文化评论 |
cinematic | screen-print | comparison | 电影对比、戏剧张力 |
Full prompt-fragment definitions: references/style-presets.md.
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 |
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 | ✓ | ✓✓ | ✓✓ | ✓✓ | ✓ | ✓✓ | ✓✓ | ✓ |
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 |
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.
refs/NN-ref-{slug}.{ext}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: directAt 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.
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 usedSlug: 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.
- [ ] 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 reportCheck 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 |
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.--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.
analysis.mdsource.md exists).references/workflows/analysis-framework.md: content type, hook potential, audience, engagement signals, visual opportunity map, swipe flow.analysis.md.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.
analysis.md.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.outline.md → Step 3.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:
prompts/NN-{type}-{slug}.md in the user's preferred language (backup rule applies), then verify all selected prompt files exist.--ref; backup rule applies to the PNG file. This establishes the anchor.--ref <path-to-image-01.png>.## Batch Generation Policy: backend native batch first, runtime parallel tool calls second, sequential only as fallback.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.
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)| 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.
| 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.
Text correction policy:
| File | Content |
|---|---|
references/confirmation.md | Verbatim AskUserQuestion copy for every confirmation path |
references/style-presets.md | Full preset shortcut definitions |
references/presets/<style>.md | Per-style element definitions |
references/palettes/<name>.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 |
EXTEND.md lives at the first matching path listed in Step 0. Three ways to change it:
references/config/preferences-schema.md.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.© guanyang, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 28 other files (references) in skills/baoyu-image-cards of guanyang/open-agent-hub.
Open the folder on GitHubat commit acd7c6c
Baoyu Image Cards next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Baoyu Image Cards this skillguanyang/open-agent-hub | 977 | — | ~6.7k | Automated safety check: Pass | MIT | |
| Data Viz Rendererzebbern/claude-code-guide | 4.7k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Image Generationonyx-dot-app/onyx | 32k | 1 repos | ~1.7k | Automated safety check: Pass | Custom licence | |
| SEO Image GeneratorAgriciDaniel/claude-seo | 19k | 2 repos | ~2.1k | Automated safety check: Pass | MIT | |
| Ecom Image2buluslan/gpt-image2-ecommerce | 410 | — | ~2.9k | Automated safety check: Pass | MIT | |
| Design Image Studiokangarooking/design-image-studio | 102 | — | ~1.5k | Automated safety check: Pass | MIT |
zebbern/claude-code-guide
Generate self-contained HTML/SVG infographics from JSON data, including stat cards, bar charts, flow diagrams, and mixed dashboards.
onyx-dot-app/onyx
Generate or edit raster images (photos, illustrations, textures, sprites, mockups, logos, infographics) using the workspace's configured image-generation provider via onyx-cli image.
AgriciDaniel/claude-seo
Generates Open Graph previews, blog hero images, product photos and infographics for SEO use through Gemini image tools and the banana extension.
buluslan/gpt-image2-ecommerce
由 buluslan(公众号:新西楼.AI)研发的开源电商做图 Skill:39 个电商场景模板、Campaign 套图一致性、GPT-Image-2.5 官方双模型路由(Flare/Sunburst)与平台技术预检。通过用户配置的 OpenAI 兼容端点生成图片,或导出 prompt 包手动使用。Trigger whenever the user wants product main…
kangarooking/design-image-studio
Directly generate design-oriented AI images with strong creative direction and prompt engineering.
charlie947/social-media-skills
Generate a branded slide-by-slide LinkedIn carousel using Gemini.
guanyang/open-agent-hub
This skill should be used when long-running agent sessions need context compression, structured summarization, compaction, token-per-task optimization, or durable handoff summaries that preserve…
guanyang/open-agent-hub
This skill should be used to explain or reason about the foundational concepts of context engineering: what context is, the anatomy of a context window, how attention mechanics work, the U-shaped…
guanyang/open-agent-hub
This skill should be used when building agent evaluation systems: deterministic checks, regression suites, multi-dimensional rubrics, quality gates, production monitoring, baseline comparison, and…
guanyang/open-agent-hub
This skill should be used when designing multi-agent systems that need context isolation, supervisor or swarm coordination, explicit handoffs, parallel execution, or a decision on whether multiple…
guanyang/open-agent-hub
This skill should be used for project-level decisions about LLM-powered systems: whether an LLM is the right primitive for the task at hand, the shape of a multi-stage batch or agent pipeline, token…
guanyang/open-agent-hub
This skill should be used for the tool-interface layer of an agent system specifically: writing tool descriptions agents can route on, designing tool schemas and response formats, naming…
Categories
Generates infographic image card series with 12 visual styles, 8 layouts, and 3 color palettes. Baoyu Image Cards is an agent skill from guanyang/open-agent-hub. Generates infographic image card series with 12 visual styles, 8 layouts, and 3 color palettes.
Baoyu Image Cards fits situations like: user mentions 小红书图片; wants social media infographic series.
Run `npx skills add guanyang/open-agent-hub --skill baoyu-image-cards -a claude-code`. Or copy the skill folder (skills/baoyu-image-cards in guanyang/open-agent-hub) into .claude/skills/baoyu-image-cards in your project. Claude Code loads it when a task matches its description.
Run `npx skills add guanyang/open-agent-hub --skill baoyu-image-cards -a codex`. Or copy the skill folder (skills/baoyu-image-cards in guanyang/open-agent-hub) into .agents/skills/baoyu-image-cards in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add guanyang/open-agent-hub --skill baoyu-image-cards -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/baoyu-image-cards, .gemini/skills/baoyu-image-cards, .github/skills/baoyu-image-cards and .opencode/skills/baoyu-image-cards in your project.
SKILL.md names no scripts, command-line tools or credentials: Baoyu Image Cards is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Baoyu Image Cards is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 6.7k tokens (SKILL.md is roughly 27k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 20k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Baoyu Image Cards: Data Viz Renderer (zebbern/claude-code-guide, 4.7k stars), Image Generation (onyx-dot-app/onyx, 32k stars), SEO Image Generator (AgriciDaniel/claude-seo, 19k stars) and Ecom Image2 (buluslan/gpt-image2-ecommerce, 410 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
guanyang (a GitHub user) maintains it in guanyang/open-agent-hub, which has 977 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on October 10, 2026.
Source: guanyang/open-agent-hub on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.