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Agent skill

Xiaohongshu

by majiayu000 in majiayu000/spellbook

生成小红书文案和配图。当用户需要写小红书、生成社交媒体文案、小红书运营内容时使用. An agent skill from majiayu000/spellbook.

MITAuto-check: notes

Install Xiaohongshu

skills CLI
$ npx skills add majiayu000/spellbook --skill xiaohongshu -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install majiayu000/spellbook xiaohongshu --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/majiayu000/spellbook.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/xiaohongshu .claude/skills/xiaohongshu && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
xiaohongshu
GitHub stars
287
Token cost
~2k tokens
SKILL.md length
391 words
Files
14 (incl. scripts)
Skills in repo
97
Repo updated
First seen
Licence
MIT

At a glance

生成小红书文案和配图。当用户需要写小红书、生成社交媒体文案、小红书运营内容时使用. An agent skill from majiayu000/spellbook.

  • Tasks that involve UI design
  • SKILL.md covers 平台硬约束, 文件组织, 完整工作流程 and Extended Reference
  • Runs Python scripts from its folder; calls python3; needs ATLAS_API_KEY and LLM_API_KEY

What it does

Xiaohongshu is an agent skill from majiayu000/spellbook. 生成小红书文案和配图。当用户需要写小红书、生成社交媒体文案、小红书运营内容时使用

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 17 other files, including scripts (for example `database/feeds.json`, `database/summary.md` and `reference/extended.md`).

It works with Xiaohongshu. The repository describes itself as: Cross-runtime skills for Claude Code, Codex, and multi-agent workflows. The licence is MIT.

When your agent uses it

  • Tasks that involve UI design

Example prompts

  • “/xiaohongshu”

Requirements

  • Python 3
  • A credential in ATLAS_API_KEY
  • A credential in LLM_API_KEY
  • Pre-approved tools (allowed-tools): WebSearch, Read, Bash, AskUserQuestion, Write, Task

What it can do on your machine

Read from SKILL.md and the folder at commit ed52af7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • WebSearch
    • Read
    • Bash
    • AskUserQuestion
    • Write
    • Task

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • ATLAS_API_KEY
    • LLM_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Xiaohongshu loads about 2k tokens when it runs. Until then it costs about 13 tokens; SKILL.md has 391 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~13
When it runs · the whole SKILL.md, loaded when a task matches
~2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: WebSearch, Read, Bash, AskUserQuestion, Write, Task

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from majiayu000/spellbook at commit ed52af7, republished under its MIT licence (© majiayu000). 391 words, ~2,050 tokens.

Download SKILL.mdSave it as .claude/skills/xiaohongshu/SKILL.md (or your agent's skills folder). This skill also uses 13 other files; get the full folder from GitHub.
name
xiaohongshu
description
生成小红书文案和配图。当用户需要写小红书、生成社交媒体文案、小红书运营内容时使用
allowed-tools
WebSearch, Read, Bash, AskUserQuestion, Write, Task
metadata.argument-hint
[内容主题或素材]

小红书内容生成器

你是一个专业的小红书内容运营专家，帮助用户从调研到发布完成全流程。

平台硬约束

约束限制
标题≤20个中文字（英文单词按1个字计，数字/标点按1个字计）
正文≤1000字
配图1-18张，推荐3:4竖版（1080x1440）
标签通过 tags 参数传入，不要写在正文里

文件组织

每篇笔记的所有产物（HTML、图片、文案）统一存放在独立目录中，防止覆盖：

<工作目录>/posts/
└── YYYYMMDD-<slug>/          # 如 20260206-opus46
    ├── cover.html            # HTML 源文件（保留，可微调重截）
    ├── cover.png             # 截图输出
    ├── features.html
    ├── features.png
    ├── ...
    └── content.md            # 文案 + 标签 + 发布元数据

目录命名规则： YYYYMMDD-<slug>

  • 日期：发布/创建日期
  • slug：2-4 个词的英文标识（如 opus46、uiux-skill、cursor-tips）

content.md 格式：

markdown
---
title: 标题
date: 2026-02-06
status: published | draft
feed_id: （发布后回填）
---

## 正文

文案内容...

## 标签

tag1, tag2, tag3, ...

工作流集成：

  • 第四步生成配图时，HTML 和 PNG 都存到该目录
  • 第五步写文案时，保存 content.md 到该目录
  • 第六步发布时，从 content.md 读取内容，图片路径用该目录的绝对路径
  • 第七步验证后，回填 feed_id 到 content.md

完整工作流程

第一步：了解需求

确认用户要发的主题和已有素材（文章、changelog、产品信息等）。判断内容领域：科技/美妆/穿搭/美食/旅游/生活/职场/母婴/健身/家居。

第二步：竞品调研 + 入库（必须执行）

这一步的目标：从竞品数据中提取标题类型、配图风格、高频标签、成功要素，直接指导后续创作。

2.1 查本地数据库
bash
python3 ~/.claude/skills/xiaohongshu/scripts/feed_database.py list --domain [领域]  # 在工作目录下执行
  • 有 ≥5 条同领域数据 → 读 ./database/summary.md，跳到 2.4
  • 不足 5 条 → 继续 2.2 从小红书补充采集
2.2 搜索 + 采集
mcp__xiaohongshu-mcp__search_feeds(keyword="[主题关键词]", filters={"sort_by": "最多点赞"})

对搜索结果中赞数 TOP 5-8 篇，获取详情：

mcp__xiaohongshu-mcp__get_feed_detail(feed_id, xsec_token)
2.3 标注 + 入库

对每篇高赞笔记提取分析维度后，写入本地数据库：

bash
python3 ~/.claude/skills/xiaohongshu/scripts/feed_database.py add '<json>'  # 在工作目录下执行

分析 JSON 模板见「高赞笔记数据库 → 分析并标注」章节。

采集完成后生成 summary：

bash
python3 ~/.claude/skills/xiaohongshu/scripts/feed_database.py analyze  # 在工作目录下执行
2.4 读取 summary 指导创作

读取 ./database/summary.md，提取以下决策依据供后续步骤使用：

决策项从 summary 取用在哪一步
标题类型标题类型分布 TOP 1第五步：写标题
配图风格配图风格分布 TOP 1第四步：生成配图
高频标签高频标签 TOP 15第三步：确定标签
成功要素高频成功要素 TOP 10第五步：写正文
收藏/赞比互动数据均值判断内容类型（高收藏 = 干货型）
第三步：确定标签（8-10个）

优先从 summary 的高频标签中选取，再结合 tag-database.md 补充：

层级数量来源
大标签（泛领域）1-2个tag-database.md
中标签（领域相关）3-4个summary 高频标签
小标签（精准长尾）2-3个summary 高频标签 + 竞品详情
情绪标签1-2个tag-database.md
第四步：生成配图

参考 summary 中的配图风格分布 TOP 1 确定基调，再用 UI/UX Pro Max Skill 获取设计系统。

步骤 1：调用 UI/UX Pro Max 获取设计系统

根据内容主题，调用设计系统生成器（67 种风格、96 种配色、57 种字体自动匹配）：

bash
python3 ~/.claude/plugins/marketplaces/ui-ux-pro-max-skill/src/ui-ux-pro-max/scripts/search.py \
  "<内容主题描述，英文>" \
  --design-system \
  -f markdown

示例：

bash
# 科技工具类
python3 ~/.claude/plugins/marketplaces/ui-ux-pro-max-skill/src/ui-ux-pro-max/scripts/search.py \
  "developer tool AI coding assistant dark tech" --design-system -f markdown

# 美妆护肤类
python3 ~/.claude/plugins/marketplaces/ui-ux-pro-max-skill/src/ui-ux-pro-max/scripts/search.py \
  "beauty skincare spa elegant feminine" --design-system -f markdown

# SaaS 产品类
python3 ~/.claude/plugins/marketplaces/ui-ux-pro-max-skill/src/ui-ux-pro-max/scripts/search.py \
  "SaaS dashboard analytics modern" --design-system -f markdown

设计系统输出包含：UI 样式、配色方案（5 色）、字体配对、关键动效、反面模式等。

也可以搜索特定域：

bash
# 只搜风格
python3 ~/.claude/plugins/marketplaces/ui-ux-pro-max-skill/src/ui-ux-pro-max/scripts/search.py \
  "glassmorphism" --domain style

# 只搜配色
python3 ~/.claude/plugins/marketplaces/ui-ux-pro-max-skill/src/ui-ux-pro-max/scripts/search.py \
  "tech startup" --domain color

# 只搜字体
python3 ~/.claude/plugins/marketplaces/ui-ux-pro-max-skill/src/ui-ux-pro-max/scripts/search.py \
  "modern minimal" --domain typography
步骤 2：基于设计系统写 HTML

拿到设计系统后，严格按照其推荐的样式、配色、字体、动效编写 HTML（1080x1440）。

⚠️ HTML 布局规范：

css
body {
  width: 1080px;
  /* ❌ 不要写 height: 1440px + overflow: hidden，会静默截断内容 */
  /* ✅ 让内容自然撑开，由截图脚本裁切 */
}
.container {
  width: 1080px;
  min-height: 1440px;
  display: flex;
  flex-direction: column;
}

封面构图原则 —— 上重下轻：

小红书信息流中，封面底部会被标题 + 作者头像遮罩覆盖（约底部 15%）。从设计构图上遵循上重下轻：

  • 上部 2/3：核心信息（大标题、数字、主视觉焦点）
  • 下部 1/3：装饰性/次要元素，被遮挡不影响阅读
  • 内容图（第 2-N 张）不受此限制

风格选择策略：

UI/UX Pro Max 输出的风格作为基础，但需要结合小红书的视觉习惯调整：

  • 30% 概率：使用高信息密度布局（Bento Grid、Dashboard 风格），适合功能汇总、工具推荐、数据对比类内容。这类封面在小红书收藏率高。
  • 70% 概率：使用 UI/UX Pro Max 推荐的风格，但封面必须增加卡片/色块/图标等视觉元素，不能只有大字+空背景。

如果 UI/UX Pro Max 推荐的风格生成封面过于简洁，主动切换为 Bento Grid 或卡片网格布局补充视觉层次。

通用设计要点：

  • 封面图：必须有视觉层次（背景+卡片+文字），数字/关键词高亮
  • 内容图：卡片布局，每张聚焦一个主题
  • 中文字体：Noto Sans SC（Google Fonts CDN），英文用设计系统推荐的字体
  • 尺寸：固定 1080x1440
步骤 3：截图（带溢出检测）

不要直接用 1080x1440 截图，内容溢出会被静默截断。使用以下流程：

bash
# 1. 大 viewport 截图（捕获完整内容）
"/Applications/Google Chrome.app/Contents/MacOS/Google Chrome" \
  --headless=new --disable-gpu --no-sandbox \
  --window-size=1080,2880 \
  --screenshot=/tmp/xhh_raw.png \
  input.html

# 2. 裁切到 1080x1440 + 溢出检测
python3 -c "
from PIL import Image
import numpy as np

img = Image.open('/tmp/xhh_raw.png')
arr = np.array(img)

# 检测 1440px 以下是否有内容
bg = arr[-1, 0, :]
below = arr[1440:, :, :]
diff = np.abs(below.astype(int) - bg.astype(int))
if np.any(diff > 20, axis=2).any():
    print('⚠️ 内容溢出 1440px！请减少内容或缩小元素尺寸')
else:
    print('✅ 内容未溢出')

# 裁切并保存
img.crop((0, 0, 1080, 1440)).save('output.png')
print(f'已保存 output.png (1080x1440)')
"

如果检测到溢出，必须修改 HTML 减少内容后重新截图，不能忽略。

方案 B：AI 生图（可选）

适合：生活、美妆、种草、情感等需要真实感或艺术风格的内容。

同样先调用 UI/UX Pro Max 获取配色和风格方向，再传给图片生成脚本：

运行前设置 ATLAS_API_KEY/LLM_API_KEY；如需从文件读取，显式传 --env-file 或设置 XHS_ENV_FILE。

bash
python3 ~/.claude/skills/xiaohongshu/scripts/generate_image.py "{prompt}" --ratio 3:4 --num 1 --output ./images
Show full SKILL.md (154 more words)Show less
第四步半：封面质量检查

封面决定用户是否点进来，必须视觉丰富，绝不能只有大字+空白背景。

封面必须满足（缺一不可）：

  • 有明确的视觉焦点（大数字、产品截图、对比图）
  • 有层次感（至少 3 层：背景 + 卡片/色块 + 文字）
  • 有色彩对比（不能全是同一个色调）
  • 信息密度适中（不空旷也不过载，1.5 秒内能抓住重点）
  • 上重下轻构图（底部 1/3 为装饰区，核心信息在上部 2/3）

封面类型选择（按内容匹配）：

类型适合结构
数字冲击型工具/数据/汇总超大数字 + 彩色标签 + 卡片网格
前后对比型效果展示左右/上下分栏 + Before/After
产品截图型软件/App模拟屏幕截图 + 标注箭头
人物+文字型经验/故事头像/插图 + 大字标题
卡片网格型多功能/资源Bento Grid 多色卡片
第五步：写文案

参考 summary 的标题类型分布 TOP 1 选择标题公式，参考高频成功要素确定正文结构。

标题公式：

  • 数字型：[数字]个[主题] 后悔没早知道（数字冲击力最强）
  • 情绪型：[主题]也太[形容词]了！
  • 热点型：[事件]一文看懂
  • 混合型：[产品] [数字]版更新汇总｜[最大亮点]

⚠️ 标题写完必须人工数字数，确保 ≤20 字。

正文规范：

  • 纯文本，不用 Markdown 语法
  • emoji 分隔段落，但不要滥用
  • 多换行，每段不超3行
  • 口语化但不失专业感，避免纯 AI 味
  • 加入个人口吻（"我把xxx全看完了"、"亲测"）
  • ≤1000字，核心干货做进图片
  • 结尾必须提问引导互动

正文结构模板：

个人叙事钩子（1-2句）
→ 核心亮点分点（❶❷❸，每点功能+用户价值）
→ 次要功能精选（简短列表）
→ 修复/注意事项（如有）
→ 行动指引（升级方法/购买链接等）
→ 互动引导结尾（提问）

文案写完后，保存到帖子目录的 content.md：

markdown
---
title: 标题
date: 2026-02-06
status: draft
---

## 正文

文案内容...

## 标签

tag1, tag2, tag3
第六步：发布

先确认登录状态：

mcp__xiaohongshu-mcp__check_login_status()

从帖子目录读取 content.md 和图片，发布：

mcp__xiaohongshu-mcp__publish_content(
  title="标题",
  content="正文（不含标签）",
  images=["<帖子目录>/cover.png", "<帖子目录>/features.png", ...],
  tags=["标签1", "标签2", ...]
)

发布成功后，更新 content.md 的 status 为 published。

发布前检查清单：

  • 标题 ≤20 字
  • 正文 ≤1000 字
  • 正文不含 # 标签（标签走 tags 参数）
  • 图片路径为绝对路径且文件存在
  • 至少1张图片
  • 已确认登录状态
  • 防限流：正文无安装命令/代码/外部链接
  • 防限流：正文非通篇产品介绍，有场景叙事（7-3 原则）
  • 防限流：无绝对化用语（最/第一/唯一）
  • 防限流：封面有视觉层次，非纯大字+空白

支持定时发布（1小时~14天内）：

schedule_at="2026-02-05T10:30:00+08:00"
第七步：验证

发布后搜索确认笔记可见：

mcp__xiaohongshu-mcp__search_feeds(keyword="标题关键词", filters={"sort_by": "最新"})

搜索到后，将 feed_id 回填到 content.md 的 frontmatter 中：

yaml
status: published
feed_id: xxx

注意：新笔记需要几分钟才能被索引，MCP 无法查看自己发布的内容，建议用户去 App 确认展示效果。

Extended Reference

Detailed material starting at ## 高赞笔记数据库 has been moved to reference/extended.md to keep this skill concise. Load that reference when the task requires the moved examples, command catalogs, checklists, platform details, or implementation templates.

© majiayu000, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 13 other files (scripts) in skills/xiaohongshu of majiayu000/spellbook.

  • SKILL.md
  • .env.example
  • database/feeds.json
  • database/summary.md
  • reference/extended.md
  • requirements.txt
  • scripts/feed_database.py
  • scripts/generate_image.py
  • styles/contrast-impact.md
  • styles/cute-illustration.md
  • styles/glass-card.md
  • styles/photo-realistic.md
  • styles/text-highlight.md
  • tag-database.md

Open the folder on GitHubat commit ed52af7

Compare with similar skills

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Guizang Social Cardsop7418/guizang-social-card-skill7.4k1 repos~7.8kAutomated safety check: PassAGPL-3.0
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    7.4k GitHub starsUsed in 1 repo~7.8k tokens
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    Builds single-file interactive HTML prototypes rendered with the real LobeHub UI components and written as production-style React, so they can later be split into files.

    83k GitHub stars~1.6k tokensUpdated today
    Frontend & DesignAuto-check passed

  • Make Interfaces Feel Better

    samuelclay/NewsBlur

    Design engineering principles for making interfaces feel polished.

    7.6k GitHub starsUsed in 10 repos~1.5k tokens
    Frontend & DesignAuto-check passed

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Works with

Questions about Xiaohongshu

What does Xiaohongshu do?

生成小红书文案和配图。当用户需要写小红书、生成社交媒体文案、小红书运营内容时使用. An agent skill from majiayu000/spellbook. Xiaohongshu is an agent skill from majiayu000/spellbook.

When should I use Xiaohongshu?

Xiaohongshu fits situations like: tasks that involve UI design.

How do I install Xiaohongshu in Claude Code?

Run `npx skills add majiayu000/spellbook --skill xiaohongshu -a claude-code`. Or copy the skill folder (skills/xiaohongshu in majiayu000/spellbook) into .claude/skills/xiaohongshu in your project. Claude Code loads it when a task matches its description.

How do I install Xiaohongshu in Codex?

Run `npx skills add majiayu000/spellbook --skill xiaohongshu -a codex`. Or copy the skill folder (skills/xiaohongshu in majiayu000/spellbook) into .agents/skills/xiaohongshu in your project. Codex loads it when a task matches its description.

Can I use Xiaohongshu in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add majiayu000/spellbook --skill xiaohongshu -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/xiaohongshu, .gemini/skills/xiaohongshu, .github/skills/xiaohongshu and .opencode/skills/xiaohongshu in your project.

What does Xiaohongshu need to run?

Going by SKILL.md and its folder, Xiaohongshu needs Python for the scripts in its folder, the command-line tools its instructions call (python3) and credentials named ATLAS_API_KEY and LLM_API_KEY. Our summary lists: Python 3; A credential in ATLAS_API_KEY; A credential in LLM_API_KEY. Its frontmatter pre-approves these tools: WebSearch, Read, Bash, AskUserQuestion, Write, Task.

Does Xiaohongshu access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Xiaohongshu safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Xiaohongshu use?

Xiaohongshu is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Xiaohongshu use?

About 2k tokens (SKILL.md is roughly 8.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Xiaohongshu?

Skills that share tags, products or a category with Xiaohongshu: Banner Design System (nextlevelbuilder/ui-ux-pro-max-skill, 135k stars), Agent Reach (Panniantong/Agent-Reach, 95k stars), UI Styling (Ohh-889/skyroc, 795 stars) and Guizang Social Cards (op7418/guizang-social-card-skill, 7.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Xiaohongshu?

majiayu000 (a GitHub user) maintains it in majiayu000/spellbook, which has 287 GitHub stars. The repository holds 97 skills in this directory. The repository was last updated on October 8, 2026.

Source: majiayu000/spellbook on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.