Baoyu Infographic
Infographics: 21 layouts x 21 styles (信息图, 可视化).
MCP get_skill({ skillId: "infographic-generator-36d966c5" })Use this skill with your agent
Create a free account and connect via MCP
# Infographic Generator
Adapted from [baoyu-infographic](https://github.com/JimLiu/baoyu-skills) for Hermes Agent's tool ecosystem.
Two dimensions: **layout** (information structure) × **style** (visual aesthetics). Freely combine any layout with any style.
## When to Use
Trigger this skill when the user asks to create an infographic, visual summary, information graphic, or uses terms like "信息图", "可视化", or "高密度信息大图". The user provides content (text, file path, URL, or topic) and optionally specifies layout, style, aspect ratio, or language.
## Options
| Option | Values |
|--------|--------|
| Layout | 21 options (see Layout Gallery), default: bento-grid |
| Style | 21 options (see Style Gallery), default: craft-handmade |
| Aspect | Named: landscape (16:9), portrait (9:16), square (1:1). Custom: any W:H ratio (e.g., 3:4, 4:3, 2.35:1) |
| Language | en, zh, ja, etc. |
## Layout Gallery
| Layout | Best For |
|--------|----------|
| `linear-progression` | Timelines, processes, tutorials |
| `binary-comparison` | A vs B, before-after, pros-cons |
| `comparison-matrix` | Multi-factor comparisons |
| `hierarchical-layers` | Pyramids, priority levels |
| `tree-branching` | Categories, taxonomies |
| `hub-spoke` | Central concept with related items |
| `structural-breakdown` | Exploded views, cross-sections |
| `bento-grid` | Multiple topics, overview (default) |
| `iceberg` | Surface vs hidden aspects |
| `bridge` | Problem-solution |
| `funnel` | Conversion, filtering |
| `isometric-map` | Spatial relationships |
| `dashboard` | Metrics, KPIs |
| `periodic-table` | Categorized collections |
| `comic-strip` | Narratives, sequences |
| `story-mountain` | Plot structure, tension arcs |
| `jigsaw` | Interconnected parts |
| `venn-diagram` | Overlapping concepts |
| `winding-roadmap` | Journey, milestones |
| `circular-flow` | Cycles, recurring processes |
| `dense-modules` | High-density modules, data-rich guides |
Full definitions: `references/layouts/<layout>.md`
## Style Gallery
| Style | Description |
|-------|-------------|
| `craft-handmade` | Hand-drawn, paper craft (default) |
| `claymation` | 3D clay figures, stop-motion |
| `kawaii` | Japanese cute, pastels |
| `storybook-watercolor` | Soft painted, whimsical |
| `chalkboard` | Chalk on black board |
| `cyberpunk-neon` | Neon glow, futuristic |
| `bold-graphic` | Comic style, halftone |
| `aged-academia` | Vintage science, sepia |
| `corporate-memphis` | Flat vector, vibrant |
| `technical-schematic` | Blueprint, engineering |
| `origami` | Folded paper, geometric |
| `pixel-art` | Retro 8-bit |
| `ui-wireframe` | Grayscale interface mockup |
| `subway-map` | Transit diagram |
| `ikea-manual` | Minimal line art |
| `knolling` | Organized flat-lay |
| `lego-brick` | Toy brick construction |
| `pop-laboratory` | Blueprint grid, coordinate markers, lab precision |
| `morandi-journal` | Hand-drawn doodle, warm Morandi tones |
| `retro-pop-grid` | 1970s retro pop art, Swiss grid, thick outlines |
| `hand-drawn-edu` | Macaron pastels, hand-drawn wobble, stick figures |
Full definitions: `references/styles/<style>.md`
## Recommended Combinations
| Content Type | Layout + Style |
|--------------|----------------|
| Timeline/History | `linear-progression` + `craft-handmade` |
| Step-by-step | `linear-progression` + `ikea-manual` |
| A vs B | `binary-comparison` + `corporate-memphis` |
| Hierarchy | `hierarchical-layers` + `craft-handmade` |
| Overlap | `venn-diagram` + `craft-handmade` |
| Conversion | `funnel` + `corporate-memphis` |
| Cycles | `circular-flow` + `craft-handmade` |
| Technical | `structural-breakdown` + `technical-schematic` |
| Metrics | `dashboard` + `corporate-memphis` |
| Educational | `bento-grid` + `chalkboard` |
| Journey | `winding-roadmap` + `storybook-watercolor` |
| Categories | `periodic-table` + `bold-graphic` |
| Product Guide | `dense-modules` + `morandi-journal` |
| Technical Guide | `dense-modules` + `pop-laboratory` |
| Trendy Guide | `dense-modules` + `retro-pop-grid` |
| Educational Diagram | `hub-spoke` + `hand-drawn-edu` |
| Process Tutorial | `linear-progression` + `hand-drawn-edu` |
Default: `bento-grid` + `craft-handmade`
## Keyword Shortcuts
When user input contains these keywords, **auto-select** the associated layout and offer associated styles as top recommendations in Step 3. Skip content-based layout inference for matched keywords.
If a shortcut has **Prompt Notes**, append them to the generated prompt (Step 5) as additional style instructions.
| User Keyword | Layout | Recommended Styles | Default Aspect | Prompt Notes |
|--------------|--------|--------------------|----------------|--------------|
| 高密度信息大图 / high-density-info | `dense-modules` | `morandi-journal`, `pop-laboratory`, `retro-pop-grid` | portrait | — |
| 信息图 / infographic | `bento-grid` | `craft-handmade` | landscape | Minimalist: clean canvas, ample whitespace, no complex background textures. Simple cartoon elements and icons only. |
## Output Structure
```
infographic/{topic-slug}/
├── source-{slug}.{ext}
├── analysis.md
├── structured-content.md
├── prompts/infographic.md
└── infographic.png
```
Slug: 2-4 words kebab-case from topic. Conflict: append `-YYYYMMDD-HHMMSS`.
## Core Principles
- Preserve source data faithfully — no summarization or rephrasing (but **strip any credentials, API keys, tokens, or secrets** before including in outputs)
- Define learning objectives before structuring content
- Structure for visual communication (headlines, labels, visual elements)
## Workflow
### Step 1: Analyze Content
**Load references**: Read `references/analysis-framework.md` from this skill.
1. Save source content (file path or paste → `source.md` using `write_file`)
- **Backup rule**: If `source.md` exists, rename to `source-backup-YYYYMMDD-HHMMSS.md`
2. Analyze: topic, data type, complexity, tone, audience
3. Detect source language and user language
4. Extract design instructions from user input
5. Save analysis to `analysis.md`
- **Backup rule**: If `analysis.md` exists, rename to `analysis-backup-YYYYMMDD-HHMMSS.md`
See `references/analysis-framework.md` for detailed format.
### Step 2: Generate Structured Content → `structured-content.md`
Transform content into infographic structure:
1. Title and learning objectives
2. Sections with: key concept, content (verbatim), visual element, text labels
3. Data points (all statistics/quotes copied exactly)
4. Design instructions from user
**Rules**: Markdown only. No new information. Preserve data faithfully. Strip any credentials or secrets from output.
See `references/structured-content-template.md` for detailed format.
### Step 3: Recommend Combinations
**3.1 Check Keyword Shortcuts first**: If user input matches a keyword from the **Keyword Shortcuts** table, auto-select the associated layout and prioritize associated styles as top recommendations. Skip content-based layout inference.
**3.2 Otherwise**, recommend 3-5 layout×style combinations based on:
- Data structure → matching layout
- Content tone → matching style
- Audience expectations
- User design instructions
### Step 4: Confirm Options
Use the `clarify` tool to confirm options with the user. Since `clarify` handles one question at a time, ask the most important question first:
**Q1 — Combination**: Present 3+ layout×style combos with rationale. Ask user to pick one.
**Q2 — Aspect**: Ask for aspect ratio preference (landscape/portrait/square or custom W:H).
**Q3 — Language** (only if source ≠ user language): Ask which language the text content should use.
### Step 5: Generate Prompt → `prompts/infographic.md`
**Backup rule**: If `prompts/infographic.md` exists, rename to `prompts/infographic-backup-YYYYMMDD-HHMMSS.md`
**Load references**: Read the selected layout from `references/layouts/<layout>.md` and style from `references/styles/<style>.md`.
Combine:
1. Layout definition from `references/layouts/<layout>.md`
2. Style definition from `references/styles/<style>.md`
3. Base template from `references/base-prompt.md`
4. Structured content from Step 2
5. All text in confirmed language
**Aspect ratio resolution** for `{{ASPECT_RATIO}}`:
- Named presets → ratio string: landscape→`16:9`, portrait→`9:16`, square→`1:1`
- Custom W:H ratios → use as-is (e.g., `3:4`, `4:3`, `2.35:1`)
Save the assembled prompt to `prompts/infographic.md` using `write_file`.
### Step 6: Generate Image
Use the `image_generate` tool with the assembled prompt from Step 5.
- Map aspect ratio to image_generate's format: `16:9` → `landscape`, `9:16` → `portrait`, `1:1` → `square`
- For custom ratios, pick the closest named aspect
- On failure, auto-retry once
- Save the resulting image URL/path to the output directory
### Step 7: Output Summary
Report: topic, layout, style, aspect, language, output path, files created.
## References
- `references/analysis-framework.md` — Analysis methodology
- `references/structured-content-template.md` — Content format
- `references/base-prompt.md` — Prompt template
- `references/layouts/<layout>.md` — 21 layout definitions
- `references/styles/<style>.md` — 21 style definitions
## Pitfalls
1. **Data integrity is paramount** — never summarize, paraphrase, or alter source statistics. "73% increase" must stay "73% increase", not "significant increase".
2. **Strip secrets** — always scan source content for API keys, tokens, or credentials before including in any output file.
3. **One message per section** — each infographic section should convey one clear concept. Overloading sections reduces readability.
4. **Style consistency** — the style definition from the references file must be applied consistently across the entire infographic. Don't mix styles.
5. **image_generate aspect ratios** — the tool only supports `landscape`, `portrait`, and `square`. Custom ratios like `3:4` should map to the nearest option (portrait in that case).Related Skills
More skills in Design, Media & Creative
Ableton Lom
Ableton Live Object Model (LOM) API reference for Python Remote Scripts and control surface development.
Accessibility Compliance
Implement WCAG 2.2 compliant interfaces with mobile accessibility, inclusive design patterns, and assistive technology support. Use when auditing accessibility, implementing ARIA patterns, building for screen readers, or ensuring inclusive user experiences.
Adobe Illustrator Scripting
Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
🎬 AI Cinema Director Skill
Direct high-fidelity cinematic video with AI — translates creative intent into technical cinematographic directives for Veo3, Kling, and Luma video models via muapi.ai
AI Clipping
Turn a long video into N viral-ready short clips with a single managed API call. Wraps muapi.ai's `/ai-clipping` endpoint, which handles transcription, highlight ranking through a virality framework (hook / emotional peak / opinion bomb / revelation / conflict / quotable / story peak / practical value), overlap dedupe, and vertical face-tracking auto-crop server-side. No local Whisper, no local LLM, no GPU.
AI Workflow Builder
Build, run, and visualize multi-step AI generation workflows. The AI architect translates natural language descriptions into connected node graphs — chain image generation, video creation, enhancement, and editing into automated pipelines.
Explore Other Categories
Skills from other categories with shared topics
Stable Diffusion Image Generation
State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.
Faiss
Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.
Nemo Curator
GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.