ImagesBridge the gap
Map a current problem, the obstacles and a desired outcome as a bridge. Label the actions that connect both sides.
Creator · JimLiu
Last updated · Sep 7, 2026
Generate professional infographics with 21 layout types and 22 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", "可视化", or "高密度信息大图".
Published by the site owner
This listing was published directly by the site owner. AI review approval and runtime verification are not implied. Review the source and audit notes before installing.
Creator · JimLiu
Last updated · Sep 7, 2026
Generate professional infographics with 21 layout types and 22 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", "可视化", or "高密度信息大图".
Published by the site owner
This listing was published directly by the site owner. AI review approval and runtime verification are not implied. Review the source and audit notes before installing.
Creator · JimLiu
Last updated · Sep 7, 2026
Generate professional infographics with 21 layout types and 22 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", "可视化", or "高密度信息大图".
Published by the site owner
This listing was published directly by the site owner. AI review approval and runtime verification are not implied. Review the source and audit notes before installing.
Creator · JimLiu
Last updated · Sep 7, 2026
Generate professional infographics with 21 layout types and 22 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", "可视化", or "高密度信息大图".
Published by the site owner
This listing was published directly by the site owner. AI review approval and runtime verification are not implied. Review the source and audit notes before installing.
Owner published · Review required
Install targets
Codex install prompt
Install the "baoyu-infographic" agent skill from https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Generate professional infographics with 21 layout types and 22 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", "可视化", or "高密度信息大图". After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"jimliu-baoyu-skills-baoyu-infographic","task":"Install baoyu-infographic","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.See what it makes
ImagesMap a current problem, the obstacles and a desired outcome as a bridge. Label the actions that connect both sides.
ImagesExplain a product development cycle from research to launch and feedback, with an unambiguous reading direction.
Supply asset profile
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Agent fit
Claude Code + OpenAI Agents + Cursor
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"
Maintenance
active
2mo since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
26K
80/100 Quality · 82/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Published by the site owner. Automated review approval and runtime verification are not implied.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Owner published · Review requiredPublished by the site owner. Automated review approval and runtime verification are not implied.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Review the pinned source before installing.
Stars
26K GitHub stars
Repo activity
26K stars, 2.9K forks
Maintenance
2mo since push
License
MIT
Install
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"Do not use when
Agent safety v2
Published by the site owner. Automated review approval and runtime verification are not implied.
Inspect the pinned source and approve installation explicitly in an isolated workspace.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20baoyu-infographic%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20baoyu-infographic%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/jimliu-baoyu-skills-baoyu-infographic/install
Agent should check
Copy prompt
Task: Use baoyu-infographic in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20baoyu-infographic%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jimliu-baoyu-skills-baoyu-infographic/install
Install command: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/jimliu-baoyu-skills-baoyu-infographic/install
LLM text format
/api/skills/jimliu-baoyu-skills-baoyu-infographic/install?format=text
Find alternatives
/api/skills/search?q=baoyu-infographic&limit=3
Agent prompt
Use baoyu-infographic for this task. Review https://www.openagentskill.com/api/skills/jimliu-baoyu-skills-baoyu-infographic/install, then install with: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"Registry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/jimliu-baoyu-skills-baoyu-infographic
LLM text
/api/registry/manifest/jimliu-baoyu-skills-baoyu-infographic?format=text
Install alias
/api/registry/install/jimliu-baoyu-skills-baoyu-infographic
Recommend
/api/registry/recommend?task=Use%20baoyu-infographic%20in%20an%20agent%20workflow&limit=3
Agent fit
Document processing
Use-case tags
Platforms
Claude Code, OpenAI Agents, Cursor
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Published by the site owner. Automated review approval and runtime verification are not implied.
Role in stack
Needs validation
Primary fit
Document processing
Trust label
Needs manual review
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Published by the site owner. Automated review approval and runtime verification are not implied.
GitHub adoption
PASS26K GitHub stars
Stars/forks activity
PASS26K stars, 2.9K forks; issue activity unavailable in current metadata
Recent maintenance
PASS2mo since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Review the pinned source before installing.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Parse messy files
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Workflow fit
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Scrape, clean, and reuse web data
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
--- name: baoyu-infographic description: Generate professional infographics with 21 layout types and 22 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", "可视化", or "高密度信息大图". version: 1.117.4 metadata: openclaw: homepage: https://github.com/JimLiu/baoyu-skills#baoyu-infographic ---
# Infographic Generator
Two dimensions: **layout** (information structure) × **style** (visual aesthetics). Freely combine any layout with any style.
## User Input Tools
When this skill prompts the user, follow this tool-selection rule (priority order):
1. **Prefer built-in user-input tools** exposed by the current agent runtime — e.g., `AskUserQuestion`, `request_user_input`, `clarify`, `ask_user`, or any equivalent. 2. **Fallback**: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question. 3. **Batching**: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.
Concrete `AskUserQuestion` references below are examples — substitute the local equivalent in other runtimes.
## Image Generation Tools
When this skill needs to render an image, resolve the backend in this order:
1. **Current-request override** — if the user names a specific backend in the current message, use it. 2. **Saved preference** — if `EXTEND.md` sets `preferred_image_backend` to a backend available right now, use it. 3. **Auto-select** (when the preference is `auto`, unset, or the pinned backend isn't available): - **Codex (`imagegen`)** — first, inspect your available-skills / tool inventory. If a skill named `imagegen` is listed, you are running inside Codex and MUST use it: invoke via the `Skill` tool with `skill: "imagegen"`, passing the saved prompt file's content (plus output path and aspect ratio per Codex `imagegen`'s own args). Codex `imagegen` is the official raster backend in that runtime and outranks any non-native skill (e.g., `baoyu-image-gen`) unless the user has explicitly pinned a different `preferred_image_backend`. - **Codex via `codex exec` (`codex-imagegen`)** — if the current runtime exposes no native `imagegen` skill but the `codex` CLI is on `PATH` with an active `codex login`, route through `baoyu-image-gen --provider codex-cli` (preferred), or — if baoyu-image-gen is unavailable — invoke the bundled wrapper directly. Details, parameters, and the runtime-discovery procedure live in [references/codex-imagegen.md](references/codex-imagegen.md) — load that file only when this branch is selected. - **Cursor (`GenerateImage`)** — if the runtime exposes a native `GenerateImage` tool, you are running inside Cursor and it outranks any non-native skill the same way Codex `imagegen` does. Two hard caveats: (a) it has no aspect-ratio parameter — state the target aspect ratio / dimensions explicitly in the prompt text passed as `description`; (b) it does not accept an output directory — it saves to a tool-managed location, so after generation copy/move the file to the skill's expected output path (e.g., `outputs/.../NN-xxx.png`). Reference images go in `reference_image_paths`. - **Other runtime-native tools** — if the runtime exposes a different native image tool (e.g., Hermes `image_generate`), use it the same way. - Otherwise, if exactly one non-native backend is installed (e.g., `baoyu-image-gen`), use it. - Otherwise (multiple non-native backends with no runtime-native tool), ask the user once — batch with any other initial questions. 4. **If none are available**, tell the user and ask how to proceed.
**⛔ Never substitute SVG, HTML, canvas, or other code-based rendering for raster image generation.** Codex `imagegen`'s own description says it should be used "when the output should be a bitmap asset rather than repo-native code or vector." If you cannot resolve a raster backend via step 3, fall through to step 4 and ask the user — do **not** silently emit SVG, write inline `<svg>` markup, or produce HTML/CSS art as a substitute. This applies even if the article/section seems "diagram-like": the consumer skill calling this rule has already decided that a raster image is what it needs.
**⛔ Never repair rendered text by painting over a generated bitmap.** Do not use ImageMagick, Pillow, Canvas, SVG, HTML/CSS, OCR scripts, or any other programmatic overlay to cover, rewrite, erase, stroke, or replace labels, headings, callouts, data values, or any other text inside an already generated infographic. If text is wrong or unclear, regenerate from a corrected prompt, switch to a layout with less on-image 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 backend receives the prompt file (or its content); the file is the reproducibility record and lets you switch backends without regenerating prompts.
Concrete tool names (`imagegen`, `GenerateImage`, `image_generate`, `baoyu-image-gen`) above are examples — substitute the local equivalents under the same rule.
## Reference Images
Users may supply reference images to guide style, palette, composition, or subject.
**Intake**: Accept via `--ref <files...>` or when the user provides file paths / pastes images in conversation. - File path(s) → copy to `refs/NN-ref-{slug}.{ext}` alongside the output - Pasted image with no path → ask the user for the path (per the User Input Tools rule above), or extract style traits verbally as a text fallback - No reference → skip this section
**Usage modes** (per reference):
| Usage | Effect | |-------|--------| | `direct` | Pass the file to the backend as a reference image | | `style` | Extract style traits (line treatment, texture, mood) and append to the prompt body | | `palette` | Extract hex colors from the image and append to the prompt body |
**Record in `prompts/infographic.md` frontmatter** when refs exist:
```yaml references: - ref_id: 01 filename: 01-ref-brand.png usage: direct ```
**At generation time**: - Verify each referenced file exists on disk - If `usage: direct` AND the chosen backend accepts reference images (e.g., `baoyu-image-gen` via `--ref`) → pass the file via the backend's ref parameter - Otherwise → embed extracted `style`/`palette` traits in the prompt text
## Confirmation Policy
Default behavior: **confirm before generation**.
- Treat explicit skill invocation, a file path, a matched keyword shortcut, `EXTEND.md` defaults, and the documented default combination as **recommendation inputs only**. None of them authorizes skipping confirmation. - Do **not** start Step 5 or Step 6 until the user confirms the combination/aspect/language/backend choices. - Skip confirmation only when the current request explicitly says to do so, for example: `--no-confirm`, "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 combination/aspect/language/backend in the next user-facing update before generating.
## Options
| Option | Values | |--------|--------| | `--layout` | 21 options (see Layout Gallery), default: bento-grid | | `--style` | 22 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) | | `--lang` | en, zh, ja, etc. | | `--no-confirm` | Skip Step 4 only when the user explicitly requests direct generation without confirmation | | `--ref <files...>` | Reference images (file paths) for style / palette / composition / subject guidance |
## Layout Gallery (21)
| 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 live at `references/layouts/<layout>.md`.
## Style Gallery (22)
| 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 | | `retro-popup-pop` | Retro popup collage, vintage UI, thick outlines, flat pop colors |
Full definitions live at `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` | | Retro Pop Guide | `dense-modules` + `retro-popup-pop` | | Educational Diagram | `hub-spoke` + `hand-drawn-edu` | | Process Tutorial | `linear-progression` + `hand-drawn-edu` |
Default combination: `bento-grid` + `craft-handmade` (fallback recommendation only — per the [Confirmation Policy](#confirmation-policy), defaults never bypass Step 4).
## Keyword Shortcuts
When the user's input contains these keywords, use the mapped layout as the leading Step 3 recommendation and promote the listed styles to the top of the Step 3 list. Skip content-based layout inference for matched keywords. Append any `Prompt Notes` to the Step 5 prompt.
| User Keyword | Layout | Recomme
Source provenance
Decision snapshot
25,722 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for baoyu-infographic, ready for a manual X post.
baoyu-infographic: Generate professional infographics with 21 layout types and 22 visual styles. Analyzes conten... 25.7K stars https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-infographic?ref=x
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@jimliu
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Owner published · Review required
Owner published · Review required
Install targets
Codex install prompt
Install the "baoyu-infographic" agent skill from https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Generate professional infographics with 21 layout types and 22 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", "可视化", or "高密度信息大图". After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"jimliu-baoyu-skills-baoyu-infographic","task":"Install baoyu-infographic","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.See what it makes
ImagesMap a current problem, the obstacles and a desired outcome as a bridge. Label the actions that connect both sides.
ImagesExplain a product development cycle from research to launch and feedback, with an unambiguous reading direction.
Supply asset profile
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Agent fit
Claude Code + OpenAI Agents + Cursor
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"
Maintenance
active
2mo since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
26K
80/100 Quality · 82/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Published by the site owner. Automated review approval and runtime verification are not implied.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Owner published · Review requiredPublished by the site owner. Automated review approval and runtime verification are not implied.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Review the pinned source before installing.
Stars
26K GitHub stars
Repo activity
26K stars, 2.9K forks
Maintenance
2mo since push
License
MIT
Install
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"Do not use when
Agent safety v2
Published by the site owner. Automated review approval and runtime verification are not implied.
Inspect the pinned source and approve installation explicitly in an isolated workspace.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20baoyu-infographic%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20baoyu-infographic%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
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Task: Use baoyu-infographic in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20baoyu-infographic%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jimliu-baoyu-skills-baoyu-infographic/install
Install command: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"
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Use baoyu-infographic for this task. Review https://www.openagentskill.com/api/skills/jimliu-baoyu-skills-baoyu-infographic/install, then install with: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"Registry metadata
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Manifest
/api/registry/manifest/jimliu-baoyu-skills-baoyu-infographic
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/api/registry/install/jimliu-baoyu-skills-baoyu-infographic
Recommend
/api/registry/recommend?task=Use%20baoyu-infographic%20in%20an%20agent%20workflow&limit=3
Agent fit
Document processing
Use-case tags
Platforms
Claude Code, OpenAI Agents, Cursor
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Published by the site owner. Automated review approval and runtime verification are not implied.
Role in stack
Needs validation
Primary fit
Document processing
Trust label
Needs manual review
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Published by the site owner. Automated review approval and runtime verification are not implied.
GitHub adoption
PASS26K GitHub stars
Stars/forks activity
PASS26K stars, 2.9K forks; issue activity unavailable in current metadata
Recent maintenance
PASS2mo since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Review the pinned source before installing.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Parse messy files
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Workflow fit
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Scrape, clean, and reuse web data
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
--- name: baoyu-infographic description: Generate professional infographics with 21 layout types and 22 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", "可视化", or "高密度信息大图". version: 1.117.4 metadata: openclaw: homepage: https://github.com/JimLiu/baoyu-skills#baoyu-infographic ---
# Infographic Generator
Two dimensions: **layout** (information structure) × **style** (visual aesthetics). Freely combine any layout with any style.
## User Input Tools
When this skill prompts the user, follow this tool-selection rule (priority order):
1. **Prefer built-in user-input tools** exposed by the current agent runtime — e.g., `AskUserQuestion`, `request_user_input`, `clarify`, `ask_user`, or any equivalent. 2. **Fallback**: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question. 3. **Batching**: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.
Concrete `AskUserQuestion` references below are examples — substitute the local equivalent in other runtimes.
## Image Generation Tools
When this skill needs to render an image, resolve the backend in this order:
1. **Current-request override** — if the user names a specific backend in the current message, use it. 2. **Saved preference** — if `EXTEND.md` sets `preferred_image_backend` to a backend available right now, use it. 3. **Auto-select** (when the preference is `auto`, unset, or the pinned backend isn't available): - **Codex (`imagegen`)** — first, inspect your available-skills / tool inventory. If a skill named `imagegen` is listed, you are running inside Codex and MUST use it: invoke via the `Skill` tool with `skill: "imagegen"`, passing the saved prompt file's content (plus output path and aspect ratio per Codex `imagegen`'s own args). Codex `imagegen` is the official raster backend in that runtime and outranks any non-native skill (e.g., `baoyu-image-gen`) unless the user has explicitly pinned a different `preferred_image_backend`. - **Codex via `codex exec` (`codex-imagegen`)** — if the current runtime exposes no native `imagegen` skill but the `codex` CLI is on `PATH` with an active `codex login`, route through `baoyu-image-gen --provider codex-cli` (preferred), or — if baoyu-image-gen is unavailable — invoke the bundled wrapper directly. Details, parameters, and the runtime-discovery procedure live in [references/codex-imagegen.md](references/codex-imagegen.md) — load that file only when this branch is selected. - **Cursor (`GenerateImage`)** — if the runtime exposes a native `GenerateImage` tool, you are running inside Cursor and it outranks any non-native skill the same way Codex `imagegen` does. Two hard caveats: (a) it has no aspect-ratio parameter — state the target aspect ratio / dimensions explicitly in the prompt text passed as `description`; (b) it does not accept an output directory — it saves to a tool-managed location, so after generation copy/move the file to the skill's expected output path (e.g., `outputs/.../NN-xxx.png`). Reference images go in `reference_image_paths`. - **Other runtime-native tools** — if the runtime exposes a different native image tool (e.g., Hermes `image_generate`), use it the same way. - Otherwise, if exactly one non-native backend is installed (e.g., `baoyu-image-gen`), use it. - Otherwise (multiple non-native backends with no runtime-native tool), ask the user once — batch with any other initial questions. 4. **If none are available**, tell the user and ask how to proceed.
**⛔ Never substitute SVG, HTML, canvas, or other code-based rendering for raster image generation.** Codex `imagegen`'s own description says it should be used "when the output should be a bitmap asset rather than repo-native code or vector." If you cannot resolve a raster backend via step 3, fall through to step 4 and ask the user — do **not** silently emit SVG, write inline `<svg>` markup, or produce HTML/CSS art as a substitute. This applies even if the article/section seems "diagram-like": the consumer skill calling this rule has already decided that a raster image is what it needs.
**⛔ Never repair rendered text by painting over a generated bitmap.** Do not use ImageMagick, Pillow, Canvas, SVG, HTML/CSS, OCR scripts, or any other programmatic overlay to cover, rewrite, erase, stroke, or replace labels, headings, callouts, data values, or any other text inside an already generated infographic. If text is wrong or unclear, regenerate from a corrected prompt, switch to a layout with less on-image 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 backend receives the prompt file (or its content); the file is the reproducibility record and lets you switch backends without regenerating prompts.
Concrete tool names (`imagegen`, `GenerateImage`, `image_generate`, `baoyu-image-gen`) above are examples — substitute the local equivalents under the same rule.
## Reference Images
Users may supply reference images to guide style, palette, composition, or subject.
**Intake**: Accept via `--ref <files...>` or when the user provides file paths / pastes images in conversation. - File path(s) → copy to `refs/NN-ref-{slug}.{ext}` alongside the output - Pasted image with no path → ask the user for the path (per the User Input Tools rule above), or extract style traits verbally as a text fallback - No reference → skip this section
**Usage modes** (per reference):
| Usage | Effect | |-------|--------| | `direct` | Pass the file to the backend as a reference image | | `style` | Extract style traits (line treatment, texture, mood) and append to the prompt body | | `palette` | Extract hex colors from the image and append to the prompt body |
**Record in `prompts/infographic.md` frontmatter** when refs exist:
```yaml references: - ref_id: 01 filename: 01-ref-brand.png usage: direct ```
**At generation time**: - Verify each referenced file exists on disk - If `usage: direct` AND the chosen backend accepts reference images (e.g., `baoyu-image-gen` via `--ref`) → pass the file via the backend's ref parameter - Otherwise → embed extracted `style`/`palette` traits in the prompt text
## Confirmation Policy
Default behavior: **confirm before generation**.
- Treat explicit skill invocation, a file path, a matched keyword shortcut, `EXTEND.md` defaults, and the documented default combination as **recommendation inputs only**. None of them authorizes skipping confirmation. - Do **not** start Step 5 or Step 6 until the user confirms the combination/aspect/language/backend choices. - Skip confirmation only when the current request explicitly says to do so, for example: `--no-confirm`, "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 combination/aspect/language/backend in the next user-facing update before generating.
## Options
| Option | Values | |--------|--------| | `--layout` | 21 options (see Layout Gallery), default: bento-grid | | `--style` | 22 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) | | `--lang` | en, zh, ja, etc. | | `--no-confirm` | Skip Step 4 only when the user explicitly requests direct generation without confirmation | | `--ref <files...>` | Reference images (file paths) for style / palette / composition / subject guidance |
## Layout Gallery (21)
| 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 live at `references/layouts/<layout>.md`.
## Style Gallery (22)
| 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 | | `retro-popup-pop` | Retro popup collage, vintage UI, thick outlines, flat pop colors |
Full definitions live at `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` | | Retro Pop Guide | `dense-modules` + `retro-popup-pop` | | Educational Diagram | `hub-spoke` + `hand-drawn-edu` | | Process Tutorial | `linear-progression` + `hand-drawn-edu` |
Default combination: `bento-grid` + `craft-handmade` (fallback recommendation only — per the [Confirmation Policy](#confirmation-policy), defaults never bypass Step 4).
## Keyword Shortcuts
When the user's input contains these keywords, use the mapped layout as the leading Step 3 recommendation and promote the listed styles to the top of the Step 3 list. Skip content-based layout inference for matched keywords. Append any `Prompt Notes` to the Step 5 prompt.
| User Keyword | Layout | Recomme
Source provenance
Decision snapshot
25,722 GitHub stars
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Install and adoption review
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Outcome reports after resolve, review, install, and one narrow run.
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Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for baoyu-infographic, ready for a manual X post.
baoyu-infographic: Generate professional infographics with 21 layout types and 22 visual styles. Analyzes conten... 25.7K stars https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-infographic?ref=x
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Owner published · Review required
Install targets
Codex install prompt
Install the "baoyu-infographic" agent skill from https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Generate professional infographics with 21 layout types and 22 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", "可视化", or "高密度信息大图". After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"jimliu-baoyu-skills-baoyu-infographic","task":"Install baoyu-infographic","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.See what it makes
ImagesMap a current problem, the obstacles and a desired outcome as a bridge. Label the actions that connect both sides.
ImagesExplain a product development cycle from research to launch and feedback, with an unambiguous reading direction.
Supply asset profile
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Agent fit
Claude Code + OpenAI Agents + Cursor
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"
Maintenance
active
2mo since push
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Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
26K
80/100 Quality · 82/100 Trust
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Review notes
Financial research output is not financial advice; require human review before any live investment decision · Published by the site owner. Automated review approval and runtime verification are not implied.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Owner published · Review requiredPublished by the site owner. Automated review approval and runtime verification are not implied.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Review the pinned source before installing.
Stars
26K GitHub stars
Repo activity
26K stars, 2.9K forks
Maintenance
2mo since push
License
MIT
Install
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"
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Install decision
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Install command
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"Do not use when
Agent safety v2
Published by the site owner. Automated review approval and runtime verification are not implied.
Inspect the pinned source and approve installation explicitly in an isolated workspace.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
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Agent should check
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Task: Use baoyu-infographic in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20baoyu-infographic%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jimliu-baoyu-skills-baoyu-infographic/install
Install command: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"
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Agent prompt
Use baoyu-infographic for this task. Review https://www.openagentskill.com/api/skills/jimliu-baoyu-skills-baoyu-infographic/install, then install with: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"Registry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/jimliu-baoyu-skills-baoyu-infographic
LLM text
/api/registry/manifest/jimliu-baoyu-skills-baoyu-infographic?format=text
Install alias
/api/registry/install/jimliu-baoyu-skills-baoyu-infographic
Recommend
/api/registry/recommend?task=Use%20baoyu-infographic%20in%20an%20agent%20workflow&limit=3
Agent fit
Document processing
Use-case tags
Platforms
Claude Code, OpenAI Agents, Cursor
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Published by the site owner. Automated review approval and runtime verification are not implied.
Role in stack
Needs validation
Primary fit
Document processing
Trust label
Needs manual review
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Published by the site owner. Automated review approval and runtime verification are not implied.
GitHub adoption
PASS26K GitHub stars
Stars/forks activity
PASS26K stars, 2.9K forks; issue activity unavailable in current metadata
Recent maintenance
PASS2mo since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Review the pinned source before installing.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Parse messy files
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Workflow fit
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Scrape, clean, and reuse web data
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
--- name: baoyu-infographic description: Generate professional infographics with 21 layout types and 22 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", "可视化", or "高密度信息大图". version: 1.117.4 metadata: openclaw: homepage: https://github.com/JimLiu/baoyu-skills#baoyu-infographic ---
# Infographic Generator
Two dimensions: **layout** (information structure) × **style** (visual aesthetics). Freely combine any layout with any style.
## User Input Tools
When this skill prompts the user, follow this tool-selection rule (priority order):
1. **Prefer built-in user-input tools** exposed by the current agent runtime — e.g., `AskUserQuestion`, `request_user_input`, `clarify`, `ask_user`, or any equivalent. 2. **Fallback**: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question. 3. **Batching**: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.
Concrete `AskUserQuestion` references below are examples — substitute the local equivalent in other runtimes.
## Image Generation Tools
When this skill needs to render an image, resolve the backend in this order:
1. **Current-request override** — if the user names a specific backend in the current message, use it. 2. **Saved preference** — if `EXTEND.md` sets `preferred_image_backend` to a backend available right now, use it. 3. **Auto-select** (when the preference is `auto`, unset, or the pinned backend isn't available): - **Codex (`imagegen`)** — first, inspect your available-skills / tool inventory. If a skill named `imagegen` is listed, you are running inside Codex and MUST use it: invoke via the `Skill` tool with `skill: "imagegen"`, passing the saved prompt file's content (plus output path and aspect ratio per Codex `imagegen`'s own args). Codex `imagegen` is the official raster backend in that runtime and outranks any non-native skill (e.g., `baoyu-image-gen`) unless the user has explicitly pinned a different `preferred_image_backend`. - **Codex via `codex exec` (`codex-imagegen`)** — if the current runtime exposes no native `imagegen` skill but the `codex` CLI is on `PATH` with an active `codex login`, route through `baoyu-image-gen --provider codex-cli` (preferred), or — if baoyu-image-gen is unavailable — invoke the bundled wrapper directly. Details, parameters, and the runtime-discovery procedure live in [references/codex-imagegen.md](references/codex-imagegen.md) — load that file only when this branch is selected. - **Cursor (`GenerateImage`)** — if the runtime exposes a native `GenerateImage` tool, you are running inside Cursor and it outranks any non-native skill the same way Codex `imagegen` does. Two hard caveats: (a) it has no aspect-ratio parameter — state the target aspect ratio / dimensions explicitly in the prompt text passed as `description`; (b) it does not accept an output directory — it saves to a tool-managed location, so after generation copy/move the file to the skill's expected output path (e.g., `outputs/.../NN-xxx.png`). Reference images go in `reference_image_paths`. - **Other runtime-native tools** — if the runtime exposes a different native image tool (e.g., Hermes `image_generate`), use it the same way. - Otherwise, if exactly one non-native backend is installed (e.g., `baoyu-image-gen`), use it. - Otherwise (multiple non-native backends with no runtime-native tool), ask the user once — batch with any other initial questions. 4. **If none are available**, tell the user and ask how to proceed.
**⛔ Never substitute SVG, HTML, canvas, or other code-based rendering for raster image generation.** Codex `imagegen`'s own description says it should be used "when the output should be a bitmap asset rather than repo-native code or vector." If you cannot resolve a raster backend via step 3, fall through to step 4 and ask the user — do **not** silently emit SVG, write inline `<svg>` markup, or produce HTML/CSS art as a substitute. This applies even if the article/section seems "diagram-like": the consumer skill calling this rule has already decided that a raster image is what it needs.
**⛔ Never repair rendered text by painting over a generated bitmap.** Do not use ImageMagick, Pillow, Canvas, SVG, HTML/CSS, OCR scripts, or any other programmatic overlay to cover, rewrite, erase, stroke, or replace labels, headings, callouts, data values, or any other text inside an already generated infographic. If text is wrong or unclear, regenerate from a corrected prompt, switch to a layout with less on-image 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 backend receives the prompt file (or its content); the file is the reproducibility record and lets you switch backends without regenerating prompts.
Concrete tool names (`imagegen`, `GenerateImage`, `image_generate`, `baoyu-image-gen`) above are examples — substitute the local equivalents under the same rule.
## Reference Images
Users may supply reference images to guide style, palette, composition, or subject.
**Intake**: Accept via `--ref <files...>` or when the user provides file paths / pastes images in conversation. - File path(s) → copy to `refs/NN-ref-{slug}.{ext}` alongside the output - Pasted image with no path → ask the user for the path (per the User Input Tools rule above), or extract style traits verbally as a text fallback - No reference → skip this section
**Usage modes** (per reference):
| Usage | Effect | |-------|--------| | `direct` | Pass the file to the backend as a reference image | | `style` | Extract style traits (line treatment, texture, mood) and append to the prompt body | | `palette` | Extract hex colors from the image and append to the prompt body |
**Record in `prompts/infographic.md` frontmatter** when refs exist:
```yaml references: - ref_id: 01 filename: 01-ref-brand.png usage: direct ```
**At generation time**: - Verify each referenced file exists on disk - If `usage: direct` AND the chosen backend accepts reference images (e.g., `baoyu-image-gen` via `--ref`) → pass the file via the backend's ref parameter - Otherwise → embed extracted `style`/`palette` traits in the prompt text
## Confirmation Policy
Default behavior: **confirm before generation**.
- Treat explicit skill invocation, a file path, a matched keyword shortcut, `EXTEND.md` defaults, and the documented default combination as **recommendation inputs only**. None of them authorizes skipping confirmation. - Do **not** start Step 5 or Step 6 until the user confirms the combination/aspect/language/backend choices. - Skip confirmation only when the current request explicitly says to do so, for example: `--no-confirm`, "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 combination/aspect/language/backend in the next user-facing update before generating.
## Options
| Option | Values | |--------|--------| | `--layout` | 21 options (see Layout Gallery), default: bento-grid | | `--style` | 22 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) | | `--lang` | en, zh, ja, etc. | | `--no-confirm` | Skip Step 4 only when the user explicitly requests direct generation without confirmation | | `--ref <files...>` | Reference images (file paths) for style / palette / composition / subject guidance |
## Layout Gallery (21)
| 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 live at `references/layouts/<layout>.md`.
## Style Gallery (22)
| 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 | | `retro-popup-pop` | Retro popup collage, vintage UI, thick outlines, flat pop colors |
Full definitions live at `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` | | Retro Pop Guide | `dense-modules` + `retro-popup-pop` | | Educational Diagram | `hub-spoke` + `hand-drawn-edu` | | Process Tutorial | `linear-progression` + `hand-drawn-edu` |
Default combination: `bento-grid` + `craft-handmade` (fallback recommendation only — per the [Confirmation Policy](#confirmation-policy), defaults never bypass Step 4).
## Keyword Shortcuts
When the user's input contains these keywords, use the mapped layout as the leading Step 3 recommendation and promote the listed styles to the top of the Step 3 list. Skip content-based layout inference for matched keywords. Append any `Prompt Notes` to the Step 5 prompt.
| User Keyword | Layout | Recomme
Source provenance
Decision snapshot
25,722 GitHub stars
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Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for baoyu-infographic, ready for a manual X post.
baoyu-infographic: Generate professional infographics with 21 layout types and 22 visual styles. Analyzes conten... 25.7K stars https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-infographic?ref=x
Listing + install path for baoyu-infographic: https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-infographic?ref=x Install: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0...
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[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-infographic?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)JimLiu
@jimliu
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Owner published · Review required
Owner published · Review required
Install targets
Codex install prompt
Install the "baoyu-infographic" agent skill from https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Generate professional infographics with 21 layout types and 22 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", "可视化", or "高密度信息大图". After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"jimliu-baoyu-skills-baoyu-infographic","task":"Install baoyu-infographic","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.See what it makes
ImagesMap a current problem, the obstacles and a desired outcome as a bridge. Label the actions that connect both sides.
ImagesExplain a product development cycle from research to launch and feedback, with an unambiguous reading direction.
Supply asset profile
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Agent fit
Claude Code + OpenAI Agents + Cursor
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"
Maintenance
active
2mo since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
26K
80/100 Quality · 82/100 Trust
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Review notes
Financial research output is not financial advice; require human review before any live investment decision · Published by the site owner. Automated review approval and runtime verification are not implied.
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Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Owner published · Review requiredPublished by the site owner. Automated review approval and runtime verification are not implied.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Review the pinned source before installing.
Stars
26K GitHub stars
Repo activity
26K stars, 2.9K forks
Maintenance
2mo since push
License
MIT
Install
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"Do not use when
Agent safety v2
Published by the site owner. Automated review approval and runtime verification are not implied.
Inspect the pinned source and approve installation explicitly in an isolated workspace.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
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Open JSON
/api/agent/resolve?task=Use%20baoyu-infographic%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20baoyu-infographic%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/jimliu-baoyu-skills-baoyu-infographic/install
Agent should check
Copy prompt
Task: Use baoyu-infographic in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20baoyu-infographic%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jimliu-baoyu-skills-baoyu-infographic/install
Install command: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/jimliu-baoyu-skills-baoyu-infographic/install
LLM text format
/api/skills/jimliu-baoyu-skills-baoyu-infographic/install?format=text
Find alternatives
/api/skills/search?q=baoyu-infographic&limit=3
Agent prompt
Use baoyu-infographic for this task. Review https://www.openagentskill.com/api/skills/jimliu-baoyu-skills-baoyu-infographic/install, then install with: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-infographic --skill "baoyu-infographic"Registry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/jimliu-baoyu-skills-baoyu-infographic
LLM text
/api/registry/manifest/jimliu-baoyu-skills-baoyu-infographic?format=text
Install alias
/api/registry/install/jimliu-baoyu-skills-baoyu-infographic
Recommend
/api/registry/recommend?task=Use%20baoyu-infographic%20in%20an%20agent%20workflow&limit=3
Agent fit
Document processing
Use-case tags
Platforms
Claude Code, OpenAI Agents, Cursor
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Published by the site owner. Automated review approval and runtime verification are not implied.
Role in stack
Needs validation
Primary fit
Document processing
Trust label
Needs manual review
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Published by the site owner. Automated review approval and runtime verification are not implied.
GitHub adoption
PASS26K GitHub stars
Stars/forks activity
PASS26K stars, 2.9K forks; issue activity unavailable in current metadata
Recent maintenance
PASS2mo since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Review the pinned source before installing.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Parse messy files
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Workflow fit
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Scrape, clean, and reuse web data
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
--- name: baoyu-infographic description: Generate professional infographics with 21 layout types and 22 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", "可视化", or "高密度信息大图". version: 1.117.4 metadata: openclaw: homepage: https://github.com/JimLiu/baoyu-skills#baoyu-infographic ---
# Infographic Generator
Two dimensions: **layout** (information structure) × **style** (visual aesthetics). Freely combine any layout with any style.
## User Input Tools
When this skill prompts the user, follow this tool-selection rule (priority order):
1. **Prefer built-in user-input tools** exposed by the current agent runtime — e.g., `AskUserQuestion`, `request_user_input`, `clarify`, `ask_user`, or any equivalent. 2. **Fallback**: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question. 3. **Batching**: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.
Concrete `AskUserQuestion` references below are examples — substitute the local equivalent in other runtimes.
## Image Generation Tools
When this skill needs to render an image, resolve the backend in this order:
1. **Current-request override** — if the user names a specific backend in the current message, use it. 2. **Saved preference** — if `EXTEND.md` sets `preferred_image_backend` to a backend available right now, use it. 3. **Auto-select** (when the preference is `auto`, unset, or the pinned backend isn't available): - **Codex (`imagegen`)** — first, inspect your available-skills / tool inventory. If a skill named `imagegen` is listed, you are running inside Codex and MUST use it: invoke via the `Skill` tool with `skill: "imagegen"`, passing the saved prompt file's content (plus output path and aspect ratio per Codex `imagegen`'s own args). Codex `imagegen` is the official raster backend in that runtime and outranks any non-native skill (e.g., `baoyu-image-gen`) unless the user has explicitly pinned a different `preferred_image_backend`. - **Codex via `codex exec` (`codex-imagegen`)** — if the current runtime exposes no native `imagegen` skill but the `codex` CLI is on `PATH` with an active `codex login`, route through `baoyu-image-gen --provider codex-cli` (preferred), or — if baoyu-image-gen is unavailable — invoke the bundled wrapper directly. Details, parameters, and the runtime-discovery procedure live in [references/codex-imagegen.md](references/codex-imagegen.md) — load that file only when this branch is selected. - **Cursor (`GenerateImage`)** — if the runtime exposes a native `GenerateImage` tool, you are running inside Cursor and it outranks any non-native skill the same way Codex `imagegen` does. Two hard caveats: (a) it has no aspect-ratio parameter — state the target aspect ratio / dimensions explicitly in the prompt text passed as `description`; (b) it does not accept an output directory — it saves to a tool-managed location, so after generation copy/move the file to the skill's expected output path (e.g., `outputs/.../NN-xxx.png`). Reference images go in `reference_image_paths`. - **Other runtime-native tools** — if the runtime exposes a different native image tool (e.g., Hermes `image_generate`), use it the same way. - Otherwise, if exactly one non-native backend is installed (e.g., `baoyu-image-gen`), use it. - Otherwise (multiple non-native backends with no runtime-native tool), ask the user once — batch with any other initial questions. 4. **If none are available**, tell the user and ask how to proceed.
**⛔ Never substitute SVG, HTML, canvas, or other code-based rendering for raster image generation.** Codex `imagegen`'s own description says it should be used "when the output should be a bitmap asset rather than repo-native code or vector." If you cannot resolve a raster backend via step 3, fall through to step 4 and ask the user — do **not** silently emit SVG, write inline `<svg>` markup, or produce HTML/CSS art as a substitute. This applies even if the article/section seems "diagram-like": the consumer skill calling this rule has already decided that a raster image is what it needs.
**⛔ Never repair rendered text by painting over a generated bitmap.** Do not use ImageMagick, Pillow, Canvas, SVG, HTML/CSS, OCR scripts, or any other programmatic overlay to cover, rewrite, erase, stroke, or replace labels, headings, callouts, data values, or any other text inside an already generated infographic. If text is wrong or unclear, regenerate from a corrected prompt, switch to a layout with less on-image 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 backend receives the prompt file (or its content); the file is the reproducibility record and lets you switch backends without regenerating prompts.
Concrete tool names (`imagegen`, `GenerateImage`, `image_generate`, `baoyu-image-gen`) above are examples — substitute the local equivalents under the same rule.
## Reference Images
Users may supply reference images to guide style, palette, composition, or subject.
**Intake**: Accept via `--ref <files...>` or when the user provides file paths / pastes images in conversation. - File path(s) → copy to `refs/NN-ref-{slug}.{ext}` alongside the output - Pasted image with no path → ask the user for the path (per the User Input Tools rule above), or extract style traits verbally as a text fallback - No reference → skip this section
**Usage modes** (per reference):
| Usage | Effect | |-------|--------| | `direct` | Pass the file to the backend as a reference image | | `style` | Extract style traits (line treatment, texture, mood) and append to the prompt body | | `palette` | Extract hex colors from the image and append to the prompt body |
**Record in `prompts/infographic.md` frontmatter** when refs exist:
```yaml references: - ref_id: 01 filename: 01-ref-brand.png usage: direct ```
**At generation time**: - Verify each referenced file exists on disk - If `usage: direct` AND the chosen backend accepts reference images (e.g., `baoyu-image-gen` via `--ref`) → pass the file via the backend's ref parameter - Otherwise → embed extracted `style`/`palette` traits in the prompt text
## Confirmation Policy
Default behavior: **confirm before generation**.
- Treat explicit skill invocation, a file path, a matched keyword shortcut, `EXTEND.md` defaults, and the documented default combination as **recommendation inputs only**. None of them authorizes skipping confirmation. - Do **not** start Step 5 or Step 6 until the user confirms the combination/aspect/language/backend choices. - Skip confirmation only when the current request explicitly says to do so, for example: `--no-confirm`, "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 combination/aspect/language/backend in the next user-facing update before generating.
## Options
| Option | Values | |--------|--------| | `--layout` | 21 options (see Layout Gallery), default: bento-grid | | `--style` | 22 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) | | `--lang` | en, zh, ja, etc. | | `--no-confirm` | Skip Step 4 only when the user explicitly requests direct generation without confirmation | | `--ref <files...>` | Reference images (file paths) for style / palette / composition / subject guidance |
## Layout Gallery (21)
| 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 live at `references/layouts/<layout>.md`.
## Style Gallery (22)
| 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 | | `retro-popup-pop` | Retro popup collage, vintage UI, thick outlines, flat pop colors |
Full definitions live at `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` | | Retro Pop Guide | `dense-modules` + `retro-popup-pop` | | Educational Diagram | `hub-spoke` + `hand-drawn-edu` | | Process Tutorial | `linear-progression` + `hand-drawn-edu` |
Default combination: `bento-grid` + `craft-handmade` (fallback recommendation only — per the [Confirmation Policy](#confirmation-policy), defaults never bypass Step 4).
## Keyword Shortcuts
When the user's input contains these keywords, use the mapped layout as the leading Step 3 recommendation and promote the listed styles to the top of the Step 3 list. Skip content-based layout inference for matched keywords. Append any `Prompt Notes` to the Step 5 prompt.
| User Keyword | Layout | Recomme
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baoyu-infographic: Generate professional infographics with 21 layout types and 22 visual styles. Analyzes conten... 25.7K stars https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-infographic?ref=x
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standard package or runtime install path
Permission surface
shell or command execution, filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
standard package or runtime install path
Permission surface
shell or command execution, filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
standard package or runtime install path
Permission surface
shell or command execution, filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness