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图像处理只读github未标认证来源可访问许可证需确认审计通过

baoyu-xhs-imagesbaoyu xhs 图片

Agent Skill

用于辅助图像生成、图片编辑、视觉素材处理或图像模型工作流。它适合让 Agent 根据文本生成图片、处理背景、整理视觉提示词或调用相关图像工具。使用时需要确认输入图片、版权来源、输出格式和模型限制;涉及人物、品牌、商品或公开展示素材时,应额外核对授权、真实性和内容合规边界。

总安装

188

周安装

8

GitHub Stars

381

下载量

66
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:baoyu-xhs-images(baoyu xhs 图片)
来源仓库:https://github.com/ynulihao/agentskillos
仓库路径:skills/baoyu-xhs-images
安装命令:
npx skills add https://github.com/ynulihao/agentskillos --skill baoyu-xhs-images
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/ynulihao/agentskillos --skill baoyu-xhs-images

简介

baoyu-xhs-images 用于辅助图像生成、编辑或视觉素材处理,适合调用图像工具生成图片。

  • 适用于需要文本转图片或背景处理的场景,如社交媒体内容制作。
  • 需确认输入图片版权、输出格式和模型限制。
  • 安装命令:npx skills add https://github.com/ynulihao/agentskillos --skill baoyu-xhs-images。
  • 涉及人物或品牌素材时,应额外核对授权和合规性。

SKILL.md

Xiaohongshu Infographic Series Generator

Break down complex content into eye-catching infographic series for Xiaohongshu with multiple style options.

Usage

# Auto-select style and layout based on content
/baoyu-xhs-images posts/ai-future/article.md

# Specify style
/baoyu-xhs-images posts/ai-future/article.md --style notion

# Specify layout
/baoyu-xhs-images posts/ai-future/article.md --layout dense

# Combine style and layout
/baoyu-xhs-images posts/ai-future/article.md --style tech --layout list

# Direct content input
/baoyu-xhs-images
[paste content]

# Direct input with options
/baoyu-xhs-images --style bold --layout comparison
[paste content]

Options

OptionDescription
--style <name>Visual style (see Style Gallery)
--layout <name>Information layout (see Layout Gallery)

Two Dimensions

DimensionControlsOptions
StyleVisual aesthetics: colors, lines, decorationscute, fresh, tech, warm, bold, minimal, retro, pop, notion
LayoutInformation structure: density, arrangementsparse, balanced, dense, list, comparison, flow

Style × Layout can be freely combined. Example: --style notion --layout dense creates an intellectual-looking knowledge card with high information density.

Style Gallery

StyleDescription
cute (Default)Sweet, adorable, girly - classic Xiaohongshu aesthetic
freshClean, refreshing, natural
techModern, smart, digital
warmCozy, friendly, approachable
boldHigh impact, attention-grabbing
minimalUltra-clean, sophisticated
retroVintage, nostalgic, trendy
popVibrant, energetic, eye-catching
notionMinimalist hand-drawn line art, intellectual

Detailed style definitions: references/styles/<style>.md

Layout Gallery

LayoutDescription
sparse (Default)Minimal information, maximum impact (1-2 points)
balancedStandard content layout (3-4 points)
denseHigh information density, knowledge card style (5-8 points)
listEnumeration and ranking format (4-7 items)
comparisonSide-by-side contrast layout
flowProcess and timeline layout (3-6 steps)

Detailed layout definitions: references/layouts/<layout>.md

Auto Selection

Content SignalsStyleLayout
Beauty, fashion, cute, girl, pinkcutesparse/balanced
Health, nature, clean, fresh, organicfreshbalanced/flow
Tech, AI, code, digital, app, tooltechdense/list
Life, story, emotion, feeling, warmwarmbalanced
Warning, important, must, criticalboldlist/comparison
Professional, business, elegant, simpleminimalsparse/balanced
Classic, vintage, old, traditionalretrobalanced
Fun, exciting, wow, amazingpopsparse/list
Knowledge, concept, productivity, SaaSnotiondense/list

File Structure

Each session creates an independent directory named by content slug:

xhs-images/{topic-slug}/
├── source-{slug}.{ext}             # Source files (text, images, etc.)
├── analysis.md                     # Deep analysis results
├── outline-style-[slug].md         # Variant A (e.g., outline-style-tech.md)
├── outline-style-[slug].md         # Variant B (e.g., outline-style-notion.md)
├── outline-style-[slug].md         # Variant C (e.g., outline-style-minimal.md)
├── outline.md                      # Final selected
├── prompts/
│   ├── 01-cover-[slug].md
│   ├── 02-content-[slug].md
│   └── ...
├── 01-cover-[slug].png
├── 02-content-[slug].png
└── NN-ending-[slug].png

Slug Generation:

  1. Extract main topic from content (2-4 words, kebab-case)
  2. Example: "AI工具推荐" → ai-tools-recommend

Conflict Resolution: If xhs-images/{topic-slug}/ already exists:

  • Append timestamp: {topic-slug}-YYYYMMDD-HHMMSS
  • Example: ai-tools exists → ai-tools-20260118-143052

Source Files: Copy all sources with naming source-{slug}.{ext}:

  • source-article.md, source-photo.jpg, etc.
  • Multiple sources supported: text, images, files from conversation

Workflow

Step 1: Analyze Content → analysis.md

Read source content, save it if needed, and perform deep analysis.

Actions:

  1. Save source content (if not already a file):

- If user provides a file path: use as-is - If user pastes content: save to source.md in target directory

  1. Read source content
  2. Deep analysis following references/analysis-framework.md:

- Content type classification (种草/干货/测评/教程/避坑...) - Hook analysis (爆款标题潜力) - Target audience identification - Engagement potential (收藏/分享/评论) - Visual opportunity mapping - Swipe flow design

  1. Detect source language
  2. Determine recommended image count (2-10)
  3. Select 3 style+layout combinations
  4. Save to analysis.md

Step 2: Generate 3 Outline Variants

Based on analysis, create three distinct style variants.

For each variant:

  1. Generate outline (outline-style-[slug].md):

- YAML front matter with style, layout, image_count - Cover design with hook - Each image: layout, core message, text content, visual concept - Written in user's preferred language - Reference: references/outline-template.md

VariantSelection LogicExample Filename
APrimary recommendationoutline-style-tech.md
BAlternative styleoutline-style-notion.md
CDifferent audience/moodoutline-style-minimal.md

All variants are preserved after selection for reference.

Step 3: User Confirms All Options

IMPORTANT: Present ALL options in a single confirmation step using AskUserQuestion. Do NOT interrupt workflow with multiple separate confirmations.

Determine which questions to ask:

QuestionWhen to Ask
Style variantAlways (required)
Default layoutOnly if user might want to override
LanguageOnly if source_language ≠ user_language

Language handling:

  • If source language = user language: Just inform user (e.g., "Images will be in Chinese")
  • If different: Ask which language to use

AskUserQuestion format:

Question 1 (Style): Which style variant?
- A: tech + dense (Recommended) - 专业科技感,适合干货
- B: notion + list - 清爽知识卡片
- C: minimal + balanced - 简约高端风格
- Custom: 自定义风格描述

Question 2 (Layout) - only if relevant:
- Keep variant default (Recommended)
- sparse / balanced / dense / list / comparison / flow

Question 3 (Language) - only if mismatch:
- 中文 (匹配原文)
- English (your preference)

After confirmation:

  1. Copy selected outline-style-[slug].mdoutline.md
  2. Update YAML front matter with confirmed options
  3. If custom style: regenerate outline with that style
  4. User may edit outline.md directly for fine-tuning

Step 4: Generate Images

With confirmed outline + style + layout:

For each image (cover + content + ending):

  1. Save prompt to prompts/NN-{type}-[slug].md (in user's preferred language)
  2. Generate image using confirmed style and layout
  3. Report progress after each generation

Image Generation Skill Selection:

  • Check available image generation skills
  • If multiple skills available, ask user preference

Session Management: If image generation skill supports --sessionId:

  1. Generate unique session ID: xhs-{topic-slug}-{timestamp}
  2. Use same session ID for all images
  3. Ensures visual consistency across generated images

Step 5: Completion Report

Xiaohongshu Infographic Series Complete!

Topic: [topic]
Style: [style name]
Layout: [layout name or "varies"]
Location: [directory path]
Images: N total

✓ analysis.md
✓ outline-style-tech.md
✓ outline-style-notion.md
✓ outline-style-minimal.md
✓ outline.md (selected: tech + dense)

Files:
- 01-cover-[slug].png ✓ Cover (sparse)
- 02-content-[slug].png ✓ Content (balanced)
- 03-content-[slug].png ✓ Content (dense)
- 04-ending-[slug].png ✓ Ending (sparse)

Image Modification

Edit Single Image

  1. Identify image to edit (e.g., 03-content-chatgpt.png)
  2. Update prompt in prompts/03-content-chatgpt.md if needed
  3. Regenerate image using same session ID

Add New Image

  1. Specify insertion position (e.g., after image 3)
  2. Create new prompt with appropriate slug
  3. Generate new image
  4. Renumber files: All subsequent images increment NN by 1
  5. Update outline.md with new image entry

Delete Image

  1. Remove image file and prompt file
  2. Renumber files: All subsequent images decrement NN by 1
  3. Update outline.md to remove image entry

Content Breakdown Principles

  1. Cover (Image 1): Hook + visual impact → sparse layout
  2. Content (Middle): Core value per image → balanced/dense/list/comparison/flow
  3. Ending (Last): CTA / summary → sparse or balanced

Style × Layout Matrix (✓✓ = highly recommended, ✓ = works well):

sparsebalanceddenselistcomparisonflow
cute✓✓✓✓✓✓
fresh✓✓✓✓✓✓
tech✓✓✓✓✓✓✓✓✓✓
warm✓✓✓✓✓✓
bold✓✓✓✓✓✓
minimal✓✓✓✓✓✓
retro✓✓✓✓✓✓
pop✓✓✓✓✓✓✓✓
notion✓✓✓✓✓✓✓✓✓✓✓✓

References

Detailed templates and guidelines in references/ directory:

  • analysis-framework.md - XHS-specific content analysis
  • outline-template.md - Outline format and examples
  • styles/<style>.md - Detailed style definitions
  • layouts/<layout>.md - Detailed layout definitions
  • base-prompt.md - Base prompt template

Notes

  • Image generation typically takes 10-30 seconds per image
  • Auto-retry once on generation failure
  • Use cartoon alternatives for sensitive public figures
  • All prompts and text use confirmed language preference
  • Maintain style consistency across all images in series

Extension Support

Custom styles and configurations via EXTEND.md.

Check paths (priority order):

  1. .baoyu-skills/baoyu-xhs-images/EXTEND.md (project)
  2. ~/.baoyu-skills/baoyu-xhs-images/EXTEND.md (user)

If found, load before Step 1. Extension content overrides defaults.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

37.4%
按下载量换算25

Claude

33.61%
按下载量换算22

Cursor

17.42%
按下载量换算11

Gemini CLI

8.48%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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