baoyu-cover-image▌
jimliu/baoyu-skills · updated Apr 8, 2026
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Generate customizable article cover images across 5 independent dimensions and 3 aspect ratios.
- ›Combines 6 image types (hero, conceptual, typography, metaphor, scene, minimal) with 10 color palettes and 7 rendering styles for fine-grained visual control
- ›Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects, plus additional ratios (4:3, 3:2, 3:4)
- ›Auto-analyzes article content to recommend dimensions, or accepts explicit flags for type, palette, rendering, text level
Cover Image Generator
Generate elegant cover images for articles with 5-dimensional customization.
Usage
# Auto-select dimensions based on content
/baoyu-cover-image path/to/article.md
# Quick mode: skip confirmation
/baoyu-cover-image article.md --quick
# Specify dimensions
/baoyu-cover-image article.md --type conceptual --palette warm --rendering flat-vector
# Style presets (shorthand for palette + rendering)
/baoyu-cover-image article.md --style blueprint
# With reference images
/baoyu-cover-image article.md --ref style-ref.png
# Direct content input
/baoyu-cover-image --palette mono --aspect 1:1 --quick
[paste content]
Options
| Option | Description |
|---|---|
--type <name> |
hero, conceptual, typography, metaphor, scene, minimal |
--palette <name> |
warm, elegant, cool, dark, earth, vivid, pastel, mono, retro, duotone |
--rendering <name> |
flat-vector, hand-drawn, painterly, digital, pixel, chalk, screen-print |
--style <name> |
Preset shorthand (see Style Presets) |
--text <level> |
none, title-only, title-subtitle, text-rich |
--mood <level> |
subtle, balanced, bold |
--font <name> |
clean, handwritten, serif, display |
--aspect <ratio> |
16:9 (default), 2.35:1, 4:3, 3:2, 1:1, 3:4 |
--lang <code> |
Title language (en, zh, ja, etc.) |
--no-title |
Alias for --text none |
--quick |
Skip confirmation, use auto-selection |
--ref <files...> |
Reference images for style/composition guidance |
Five Dimensions
| Dimension | Values | Default |
|---|---|---|
| Type | hero, conceptual, typography, metaphor, scene, minimal | auto |
| Palette | warm, elegant, cool, dark, earth, vivid, pastel, mono, retro, duotone | auto |
| Rendering | flat-vector, hand-drawn, painterly, digital, pixel, chalk, screen-print | auto |
| Text | none, title-only, title-subtitle, text-rich | title-only |
| Mood | subtle, balanced, bold | balanced |
| Font | clean, handwritten, serif, display | clean |
Auto-selection rules: references/auto-selection.md
Galleries
Types: hero, conceptual, typography, metaphor, scene, minimal → Details: references/types.md
Palettes: warm, elegant, cool, dark, earth, vivid, pastel, mono, retro, duotone → Details: references/palettes/
Renderings: flat-vector, hand-drawn, painterly, digital, pixel, chalk, screen-print → Details: references/renderings/
Text Levels: none (pure visual) | title-only (default) | title-subtitle | text-rich (with tags) → Details: references/dimensions/text.md
Mood Levels: subtle (low contrast) | balanced (default) | bold (high contrast) → Details: references/dimensions/mood.md
Fonts: clean (sans-serif) | handwritten | serif | display (bold decorative) → Details: references/dimensions/font.md
File Structure
Output directory per default_output_dir preference:
same-dir:{article-dir}/imgs-subdir:{article-dir}/imgs/independent(default):cover-image/{topic-slug}/
<output-dir>/
├── source-{slug}.{ext} # Source files
├── refs/ # Reference images (if provided)
│ ├── ref-01-{slug}.{ext}
│ └── ref-01-{slug}.md # Description file
├── prompts/cover.md # Generation prompt
└── cover.png # Output image
Slug: 2-4 words, kebab-case. Conflict: append -YYYYMMDD-HHMMSS
Workflow
Progress Checklist
Cover Image Progress:
- [ ] Step 0: Check preferences (EXTEND.md) ⛔ BLOCKING
- [ ] Step 1: Analyze content + save refs + determine output dir
- [ ] Step 2: Confirm options (6 dimensions) ⚠️ unless --quick
- [ ] Step 3: Create prompt
- [ ] Step 4: Generate image
- [ ] Step 5: Completion report
Flow
Input → [Step 0: Preferences] ─┬─ Found → Continue
└─ Not found → First-Time Setup ⛔ BLOCKING → Save EXTEND.md → Continue
↓
Analyze + Save Refs → [Output Dir] → [Confirm: 6 Dimensions] → Prompt → Generate → Complete
↓
(skip if --quick or all specified)
Step 0: Load Preferences ⛔ BLOCKING
Check EXTEND.md existence (priority: project → user):
# macOS, Linux, WSL, Git Bash
test -f .baoyu-skills/baoyu-cover-image/EXTEND.md && echo "project"
test -f "${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-cover-image/EXTEND.md" && echo "xdg"
test -f "$HOME/.baoyu-skills/baoyu-cover-image/EXTEND.md" && echo "user"
# PowerShell (Windows)
if (Test-Path .baoyu-skills/baoyu-cover-image/EXTEND.md) { "project" }
$xdg = if ($env:XDG_CONFIG_HOME) { $env:XDG_CONFIG_HOME } else { "$HOME/.config" }
if (Test-Path "$xdg/baoyu-skills/baoyu-cover-image/EXTEND.md") { "xdg" }
if (Test-Path "$HOME/.baoyu-skills/baoyu-cover-image/EXTEND.md") { "user" }
| Result | Action |
|---|---|
| Found | Load, display summary → Continue |
| Not found | ⛔ Run first-time setup (references/config/first-time-setup.md) → Save → Continue |
CRITICAL: If not found, complete setup BEFORE any other steps or questions.
Step 1: Analyze Content
- Save reference images (if provided) → references/workflow/reference-images.md
- Save source content (if pasted, save to
source.md) - Analyze content: topic, tone, keywords, visual metaphors
- Deep analyze references ⚠️: Extract specific, concrete elements (see reference-images.md)
- Detect language: Compare source, user input, EXTEND.md preference
- Determine output directory: Per File Structure rules
⚠️ People in Reference Images:
If reference images contain people who should appear in the cover:
- Model supports
--ref(default): Copy image torefs/, pass via--refat generation. No description file needed — the model sees the face directly. - Model does NOT support
--ref(Jimeng, Seedream 3.0): Createrefs/ref-NN-{slug}.mdwith per-character description (hair, glasses, skin tone, clothing). Embed as MUST/REQUIRED instructions in prompt text.
See reference-images.md for full decision table.
Step 2: Confirm Options ⚠️
MUST use AskUserQuestion tool to present options as interactive selection — NOT plain text tables. Present up to 4 questions in a single AskUserQuestion call (Type, Palette, Rendering, Font + Settings). Each question shows the recommended option first with reason, followed by alternatives.
Full confirmation flow and question format: references/workflow/confirm-options.md
| Condition | Skipped | Still Asked |
|---|---|---|
--quick or quick_mode: true |
6 dimensions | Aspect ratio (unless --aspect) |
All 6 + --aspect specified |
All | None |
Step 3: Create Prompt
Save to prompts/cover.md. Template: references/workflow/prompt-template.md
CRITICAL - References in Frontmatter:
- Files saved to
refs/→ Add to frontmatterreferenceslist - Style extracted verbally (no file) → Omit
references, describe in body - Before writing → Verify:
test -f refs/ref-NN-{slug}.{ext}
Reference elements in body MUST be detailed, prefixed with "MUST"/"REQUIRED", with integration approach.
Step 4: Generate Image
- Backup existing
cover.pngif regenerating - Check image generation skills; if multiple, ask preference
- Process references from prompt frontmatter:
directusage → pass via--ref(use ref-capable backend)style/palette→ extract traits, append to prompt
- Generate: Call skill with prompt file, output path, aspect ratio
- On failure: auto-retry once
Step 5: Completion Report
Cover Generated!
Topic: [topic]
Type: [type] | Palette: [palette] | Rendering: [rendering]
Text: [text] | Mood: [mood] | Font: [font] | Aspect: [ratio]
Title: [title or "visual only"]
Language: [lang] | Watermark: [enabled/disabled]
References: [N images or "extracted style" or "none"]
Location: [directory path]
Files:
✓ source-{slug}.{ext}
✓ prompts/cover.md
✓ cover.png
Image Modification
| Action | Steps |
|---|---|
| Regenerate | Backup → Update prompt file FIRST → Regenerate |
| Change dimension | Backup → Confirm new value → Update prompt → Regenerate |
Composition Principles
- Whitespace: 40-60% breathing room
- Visual anchor: Main element centered or offset left
- Characters: Simplified silhouettes; NO realistic humans
- Title: Use exact title from user/source; never invent
Extension Support
Custom configurations via EXTEND.md. See Step 0 for paths.
Supports: Watermark | Preferred dimensions | Default aspect/output | Quick mode | Custom palettes | Language
Schema: references/config/preferences-schema.md
References
Dimensions: text.md | mood.md | font.md Palettes: references/palettes/ Renderings: references/renderings/ Types: references/types.md Auto-Selection: references/auto-selection.md Style Presets: references/style-presets.md Compatibility: references/compatibility.md Visual Elements: references/visual-elements.md Workflow: confirm-options.md | prompt-template.md | reference-images.md Config: preferences-schema.md | first-time-setup.md | watermark-guide.md
How to use baoyu-cover-image on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add baoyu-cover-image
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches baoyu-cover-image from GitHub repository jimliu/baoyu-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate baoyu-cover-image. Access the skill through slash commands (e.g., /baoyu-cover-image) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★29 reviews- ★★★★★Shikha Mishra· Dec 24, 2024
baoyu-cover-image is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Fatima Choi· Dec 12, 2024
baoyu-cover-image fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Rahul Santra· Nov 15, 2024
baoyu-cover-image fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Fatima Robinson· Nov 3, 2024
baoyu-cover-image is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Yusuf Abebe· Oct 22, 2024
Solid pick for teams standardizing on skills: baoyu-cover-image is focused, and the summary matches what you get after install.
- ★★★★★Pratham Ware· Oct 6, 2024
baoyu-cover-image has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Daniel Sethi· Sep 17, 2024
Keeps context tight: baoyu-cover-image is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Ira Jackson· Sep 13, 2024
baoyu-cover-image reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Sophia Desai· Sep 5, 2024
We added baoyu-cover-image from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★William Thompson· Aug 24, 2024
baoyu-cover-image reduced setup friction for our internal harness; good balance of opinion and flexibility.
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