Xhs Writer

What it does

Example prompts

• “/xhs-writer”

Requirements

• Python 3
• A Bash shell
• A credential in OPENAI_API_KEY

Workflow steps

11 steps, taken from the step headings in SKILL.md.

1. 1Intake(必问，一次问完)
2. 25 — 卖点/亮点分析（推荐执行）
3. 3素材清点(有素材才做)
4. 4采集外部参考(观点类 / 资讯类必做；纯素材驱动可跳过)
5. 5写长文原稿(2000-4000 字)
6. 6去 AI 化
7. 75 — 图生图处理（有真实素材时必做）
8. 8分发：图文 or 视频
9. 9caption + hashtags + 标题
10. 10落盘
11. 11校验(强制)

What it can do on your machine

Read from SKILL.md and the folder at commit 6adef3b. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships 1 file in scripts/ (Shell, from the files we listed), 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:

  • OPENAI_API_KEY

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

Context cost

Xhs Writer loads about 2.3k tokens when it runs, and up to ~16k if it reads all its reference files. Until then it costs about 57 tokens; SKILL.md has 515 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~57

When it runs · the whole SKILL.md, loaded when a task matches

~2.3k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~16k

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

• NoteMentions a .env fileSKILL.md:271

  配置：在 `~/.claude/skills/xhs-writer-skill/.env` 填入 `OPENAI_API_KEY`

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 JuneYaooo/xhs-writer-skill at commit 6adef3b, republished under its Apache-2.0 licence (© JuneYaooo). 515 words, ~2,276 tokens.

name

xhs-writer

description

生成小红书(RedNote)笔记：把主题或用户提供的素材(文字/图片/视频)做成一套竖版卡片(图文) 或一段带分镜脚本的视频稿(视频)，配 caption + hashtags，落盘到 output/小红书/。 使用时机：用户说 写小红书 / 做小红书笔记 / 小红书图文 / 小红书种草 / 出一套 xhs 卡片 / 小红书视频 / write a Xiaohongshu note / make a RedNote post。

## 卖点/亮点分析结果

| 点 | 稀缺性 | 实用性 | 可感知 | 得分 | 优先级 |
|---|---|---|---|---|---|
| 亮点A | 5 | 5 | 5 | 125 | 🥇 核心 |
| 亮点B | 2 | 3 | 3 | 18 | 🥉 辅助 |

**核心卖点/亮点**：亮点A（聚焦这个，其他作为辅助）

python3 scripts/analyze_material.py <path>... \
  --out <work-dir>/reference/materials.json \
  --frames-dir <work-dir>/reference/frames

# 使用本项目的 image_generator
import sys
sys.path.insert(0, '~/.claude/skills/xhs-writer-skill/scripts')
from image_generator import GptImage2Generator

generator = GptImage2Generator(aspect_ratio="9:16")

# 图生图：保留真实素材 + 叠加小红书风格文字
generator.generate_scene_image(
    scene_data={
        'index': 1,
        'image_prompt': """Based on the reference image, create a Xiaohongshu style card, 9:16 vertical.

Keep the original image visible.

Add overlays:
- Top: "{标题}"
- Bottom: "{引导文字}"

Style:
- Keep original clear
- Casual Xiaohongshu style
- Authentic feel"""
    },
    output_path='output.jpg',
    size='auto',
    reference_image_path='material.jpg'
)

output/小红书/{YYYY-MM-DD}/{短标题}_{YYYYMMDDHHmm}/
├── {完整标题}.md        # 长文原稿
├── meta.json            # 元数据(卡片 / 分镜 / caption / hashtags / materials)
├── images/              # (图文)最终卡图 / (视频)封面
└── reference/           # materials.json / 搜索结果 / summary / 思考过程

python3 scripts/normalize_slug.py "原始长标题" --with-ts

python3 scripts/validate_meta.py <work-dir>/meta.json

# 添加路径
import sys
sys.path.insert(0, '~/.claude/skills/xhs-writer-skill/scripts')
from image_generator import GptImage2Generator

# 初始化
generator = GptImage2Generator(aspect_ratio="9:16")

# 生成
generator.generate_scene_image(
    scene_data={'index': 1, 'image_prompt': '...'},
    output_path='output.jpg',
    size='auto',
    reference_image_path='material.jpg'  # 图生图模式
)

# 用户说："帮我推广这个项目 /path/to/project"

# Step 0.5: 卖点分析
# → 列出功能，让用户打分（稀缺性×实用性×可感知）
# → 选出核心卖点

# Step 1: 素材盘点
# → 扫描项目截图、对比图、演示图
# → 分类：对比图（最有价值）> 功能演示 > 其他

# Step 4.5: 图生图
# → 对比图用图生图（保留真实感 + 小红书风格）
# → 纯文字卡片用 AI 生图（素人感）

# Step 6: 生成标题（5个选项）
# → 痛点式、提问式、发现式、热点词、身份共鸣

# 输出：6-7张卡片 + caption + hashtags

# 用户说："写一条关于 XX 好物推荐的小红书笔记"

# Step 0: Intake
# → 确认主题、目标读者、输出形态

# Step 0.5: 亮点分析
# → 这个好物的核心亮点是什么？

# Step 1: 素材盘点
# → 产品图、使用场景图、效果对比图

# Step 3-4: 写长文 + 去 AI 化

# Step 5: 拆成卡片
# → 封面（提问/发现式）+ 亮点展示 + 使用场景 + 真实体验 + CTA

# 输出：5-7张卡片 + caption + hashtags

# 用户说："写一条关于 XX 知识的小红书笔记"

# Step 0: Intake
# → 确认主题、目标读者、知识点

# Step 2: 采集外部参考
# → 搜索相关资料，交叉验证

# Step 3-4: 写长文 + 去 AI 化

# Step 5: 拆成卡片（纯文字）
# → 用 AI 生图（素人感设计）
# → 结构：封面 + 核心概念 + 步骤/要点 + 注意事项 + CTA

# Step 6: caption + hashtags

# 输出：5-7张卡片 + caption + hashtags

© JuneYaooo, Apache-2.0. 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 26 other files (scripts, references) in the repository root of JuneYaooo/xhs-writer-skill.

• SKILL.md
• .env.example
• .gitignore
• LICENSE
• README.md
• agents/openclaw.yaml
• docs/assets/demo-comparison.jpg
• docs/assets/demo-styles.jpg
• docs/assets/input-github-screenshot.jpg
• docs/assets/input-style-gallery.jpg
• docs/install.md
• install_as_skill.sh
• references/humanizer-zh.md
• references/image-sourcing.md
• references/material-intake.md
• references/meta-schema.md
• references/output-spec.md
• … and 10 more

Open the folder on GitHubat commit 6adef3b