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Social Cover Image

Community
bozhouDev
social-cover-image

Generates social cover images for articles, banners, and social posts with 5 dimensions (type, palette, rendering, text, mood) combining 10 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create social cover", "make banner", or "make cover".

Overview

PublisherbozhouDev
Repositorybozhou-skills
Skill namesocial-cover-image
Stars
78
Forks
7
Bundled files
33
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 33 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by bozhouDev on GitHub. Read the source before you install it.

Installation

Install the Social Cover Image AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/bozhouDev/bozhou-skills/tree/main/social-cover-image
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/bozhouDev/bozhou-skills.git /tmp/bozhou-skills
mkdir -p .claude/skills
cp -r /tmp/bozhou-skills/social-cover-image .claude/skills/social-cover-image
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Social Cover Image in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Social Cover Image on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Social Cover Image is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Social Cover Image Generator

Generate elegant social cover images with 5-dimensional customization.

Usage

bash
# Auto-select dimensions based on content
/social-cover-image path/to/article.md

# Quick mode: skip confirmation
/social-cover-image article.md --quick

# Specify dimensions
/social-cover-image article.md --type conceptual --palette warm --rendering flat-vector

# Style presets (shorthand for palette + rendering)
/social-cover-image article.md --style blueprint

# With reference images
/social-cover-image article.md --ref style-ref.png

# Direct content input
/social-cover-image --palette mono --aspect 1:1 --quick
[paste content]

Options

OptionDescription
--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, 5:2, 4:3, 3:2, 1:1, 3:4
--lang <code>Title language (en, zh, ja, etc.)
--no-titleAlias for --text none
--quickSkip confirmation, use auto-selection
--ref <files...>Reference images for style/composition guidance

Platform Aspect Guide

Use platform-specific aspect ratios when the publication target is known:

PlatformRecommended RatioNotes
WeChat article header2.35:1Best fit for WeChat public account article covers and blog headers
X header / social banner5:2Auto: generates at 2.35:1 with safe-zone prompt, then crops to 5:2 via ImageMagick
General-purpose cover16:9Good default for mixed channels, slides, and thumbnails
Square social card1:1Best for square-first social placements

Examples:

bash
# WeChat public account article cover
/social-cover-image article.md --aspect 2.35:1

# X article cover (auto generates 2.35:1 + crops to 5:2)
/social-cover-image article.md --aspect 5:2

Five Dimensions

DimensionValuesDefault
Typehero, conceptual, typography, metaphor, scene, minimalauto
Palettewarm, elegant, cool, dark, earth, vivid, pastel, mono, retro, duotoneauto
Renderingflat-vector, hand-drawn, painterly, digital, pixel, chalk, screen-printauto
Textnone, title-only, title-subtitle, text-richtitle-only
Moodsubtle, balanced, boldbalanced
Fontclean, handwritten, serif, displayclean

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:

  • imgs-subdir (default): {article-dir}/imgs/{article-title}/
  • same-dir: {article-dir}/
  • independent: 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 (config.yaml) ⛔ 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 config.yaml → Continue
        ↓
Analyze + Save Refs → [Output Dir] → [Confirm: 6 Dimensions] → Prompt → Generate → Complete
                                              ↓
                                     (skip if --quick or all specified)

Step 0: Load Preferences ⛔ BLOCKING

Check config.yaml existence in skill directory:

bash
SKILL_DIR="$(dirname "$(readlink -f "$0")")"  # or known skill path
test -f "${SKILL_DIR}/config.yaml" && echo "found"

The config file is located at: .claude/skills/social-cover-image/config.yaml

ResultAction
FoundLoad, 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

  1. Save reference images (if provided) → references/workflow/reference-images.md
  2. Save source content (if pasted, save to source.md)
  3. Analyze content: topic, tone, keywords, visual metaphors
  4. Deep analyze references ⚠️: Extract specific, concrete elements (see reference-images.md)
    • If references contain people → set usage: direct so model sees reference image, describe character features for stylized preservation (see reference-images.md § Character Analysis)
  5. Detect language: Compare source, user input, config.yaml preference
  6. Determine output directory: Per File Structure rules

Step 2: Confirm Options ⚠️

Full confirmation flow: references/workflow/confirm-options.md

ConditionSkippedStill Asked
--quick or quick_mode: true6 dimensionsAspect ratio (unless --aspect)
All 6 + --aspect specifiedAllNone

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 frontmatter references list
  • 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

  1. Backup existing cover.png if regenerating
  2. Use image-gen skill for image generation:
    bash
    IMAGE_GEN_SKILL=".claude/skills/image-gen"
    npx -y bun ${IMAGE_GEN_SKILL}/scripts/main.ts \
      --promptfiles prompts/cover.md \
      --image <output_path>/cover.png \
      --ar <ratio> \
      --quality 2k
    • image-gen manages its own API keys via ~/.skills/.env
    • Provider auto-detection: Google → OpenAI → DashScope
  3. Process references from prompt frontmatter:
    • direct usage → pass via --ref flag to image-gen
    • style/palette → extract traits, append to prompt
  4. 5:2 aspect ratio handling (X article cover):
    • Step 3 prompt: Append safe-zone instruction to prompt body:
      CRITICAL LAYOUT CONSTRAINT: All text, titles, and key visual elements MUST be
      placed within the vertical center 70% of the image. Leave the top 15% and bottom
      15% as decorative margins only (background patterns, gradients, or empty space).
      This is required because the image will be cropped to 5:2 aspect ratio.
    • Generate at --ar 2.35:1 (closest native ratio to 5:2)
    • Crop to 5:2 with ImageMagick:
      bash
      magick <output_path>/cover.png -gravity center -crop "%[fx:w]x%[fx:w*2/5]+0+0" +repage <output_path>/cover.png
  5. 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

ActionSteps
RegenerateBackup → Update prompt file FIRST → Regenerate
Change dimensionBackup → 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

Configuration

User preferences stored in config.yaml within the skill directory (.claude/skills/social-cover-image/config.yaml).

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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Social Cover Image AI skill do?

Generates social cover images for articles, banners, and social posts with 5 dimensions (type, palette, rendering, text, mood) combining 10 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create social cover", "make banner", or "make cover".

Why use Social Cover Image on TypingMind?

Because you install it once and use it with any model. Social Cover Image is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Social Cover Image in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bozhouDev/bozhou-skills/tree/main/social-cover-image. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Social Cover Image?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Social Cover Image?

As many as you like. As long as a model supports skills, you can use Social Cover Image with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Social Cover Image AI skill free?

It is published on GitHub by bozhouDev. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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