piekill

Xiaohongshu Search Summarizer

知识管理v1.0.3
作者:piekill更新于 2026-05-11共 4 个版本 · 最新版本发布于 2026-03-10xiaohongshu-search-summarizer
#Summarize#小红书

据 AlphaMoat 统计,截至 2026-09,Xiaohongshu Search Summarizer 累计下载 4,717 次、获 8 个星标,在全部 5,078 个 AI 技能中排名第 2,007 位,在「知识管理」分类(442 个)中排名第 191 位。

累计安装
158
累计下载
4,717
星标
8
全站排名
#2,007
全站前 40% · 「知识管理」前 44%
平台累计安装累计下载星标评论
ClawHub ↗1584,7178-

各平台的计数口径不同,统计时间不一致。

这个技能是做什么的

可提取帖文文字、图片和评论,再汇总成综合报告;流程使用浏览器并把抓取内容和图片保存到本地。抓取内容不应直接视为可靠事实,重要结论需独立核实,输出文件应放在指定目录并审阅后再分享。 需要 playwright-cli、Python 和 requests。使用不含路径分隔符的简单关键词及独立目录,所需登录应获授权后人工完成。实际查看下载图片后才能声称做了视觉分析,不假定所有帖子或登录挑战都可访问。max_posts 限 1–50。

资料发布于 2026-10-27

可以用来做什么

  • 收集某主题的帖子、图片和评论
  • 汇总小红书内容并整理研究报告

什么时候用

  • 需要围绕明确关键词进行小红书主题研究时

示例提示词

以下是根据技能文档生成的示例,不代表实际运行结果。

为这个关键词规划小红书内容研究流程,只输出步骤,不访问网页。
说明如何审阅抓取的帖子和图片并核实重要结论。

月度数据趋势

累计下载4,717
2,8863,8704,8532026-03 · 累计下载 3,0222026-05 · 累计下载 3,8522026-06 · 累计下载 4,0552026-07 · 累计下载 4,4182026-08 · 累计下载 4,5922026-09 · 累计下载 4,71726-0326-09
星标8
7882026-03 · 星标 72026-05 · 星标 72026-06 · 星标 72026-07 · 星标 82026-08 · 星标 82026-09 · 星标 826-0326-09

2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。

月份累计下载环比星标
2026-094,717—8
2026-084,592+3.9%8
2026-074,418+9.0%8
2026-064,055+5.3%7
2026-053,852—7
2026-033,022—7

SKILL.md 原文

以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。

5.5 KB · ClawHub v1.0.3
---
name: xiaohongshu-search-summarizer
description: Searches Xiaohongshu(小红书) for a given keyword, extracts the top N posts (including texts, images, and user comments), and then synthesizes a comprehensive final analytical report. Use this skill whenever the user wants to search Xiaohongshu for a specific topic, compile research seamlessly combining text and images, or needs an aggregated thematic summary of social media posts, comments, and visual data on a given subject.
compatibility: Requires playwright-cli and python3, and the Python 'requests' package installed.
---

# Xiaohongshu Search and Summarize

This skill automates the process of extracting high-quality multi-modal content (text + images) from Xiaohongshu (小红书) and actively assists you in generating a deeply integrated, analytical final report for the user. Due to Xiaohongshu's aggressive anti-scraping mechanisms, direct HTTP requests or naive scraping often result in 404s or blocks. This skill natively bypasses these by simulating a real user through the `playwright-cli` in a headed browser window.
展开全部(共 75 行)
It operates in two distinct phases:

### Phase 1: Subagent Data Collection
1. Simulate a search for the keyword on Xiaohongshu in a headed browser.
2. Advance through image sliders to fully load all lazy pictures from the top N posts.
3. Extract titles, descriptions, top comments, and all high-resolution images.
4. Download those images to a local directory and generate a raw data document (`[keyword]_raw_data.md`).

### Phase 2: AI Multi-Modal Synthesis (Your Job)
5. **You** MUST use your file reading capabilities to read the `[keyword]_raw_data.md` file.
6. Inside the raw data markdown, you will find paths to image files. **You MUST use your file reading / vision capabilities on these image file paths** to actually ingest and "see" their visual content. If you skip this step, you are only reading file names, not the images themselves!
7. **You** analyze the texts, summarize the genuinely useful comments (discarding noise like "pm me"), and interpret the semantic content of the images you just viewed (e.g. diagrams, guidelines, step-by-step UI flows).
8. **You** compile everything into a beautifully synthesized, single comprehensive report rather than just a linear list of posts. 

### Dependencies
- `playwright-cli` (Must be available on the path)
- `python3` (Required to download images and stitch the raw data markdown)
- `requests` Python package (`pip install requests`) — used by `parse.py` to download images

---

## Usage Instructions

### Step 1: Run the Extraction Script

Execute the wrapper script in `scripts/run.sh`. It accepts the following arguments:

```bash
/bin/bash <skill_dir>/scripts/run.sh "YOUR KEYWORD" <MAX_POSTS> <OUTPUT_DIRECTORY>
```

- **`YOUR KEYWORD`**: The search term to look up on Xiaohongshu.
- **`<MAX_POSTS>`**: (Optional, default = 10) The number of top posts to scan.
- **`<OUTPUT_DIRECTORY>`**: (Optional, default = `./`) Directory where the raw data and images will be saved.

**Example execution**:

```bash
/bin/bash ~/.claude/skills/xiaohongshu-search-summarizer/scripts/run.sh "openclaw使用场景" 10 "./xhs_report_openclaw_scenarios"
```

### Step 2: Read Raw Data & Images

Once the bash script finishes successfully, navigate to the `OUTPUT_DIRECTORY` and use your file reading capabilities to ingest the generated `[keyword]_raw_data.md` file.

Inside this file, you will find descriptions, comments, and file paths pointing to `post_X_img_Y.webp` or `post_X_img_Y.jpg`. 

### Step 3: Synthesis & Summarization

**This is the most critical step.** Do not just return the raw markdown file to the user. Instead, write a polished comprehensive markdown report that reorganizes the information logically, while retaining a high level of detail.

Follow these strict compilation rules:
- **Do not list posts individually** (e.g. avoid "Post 1: ... Post 2: ...").  
- **Read the Images:** You MUST use your file reading and vision capabilities on the `.webp` or `.jpg` image files found in the raw data directory to interpret their contents.
- **Detailed & Comprehensive Synthesis:** Provide a highly detailed summary that includes diverse viewpoints, nuances, and specific examples found across different posts. Avoid over-summarizing or losing important context; preserve the richness and diversity of the information.
- **Extract and merge themes:** Group ideas by concepts, steps, recurring themes, or pros/cons.  
- **Evaluate comments:** Merge insights from valuable comments directly into the core narrative. Skip useless or repetitive comments, but preserve diverse opinions or helpful counter-arguments from the comments section.
- **Integrate images contextually:** Embed the most relevant and high-quality images directly into the flow of your final report to support the analytical points being made. Describe their visual meaning based on what you saw with your vision capabilities.
- **Save to OUTPUT_DIRECTORY:** Save your beautifully compiled final Markdown report using your file writing capabilities directly into the same `<OUTPUT_DIRECTORY>` as the raw data (e.g., `<OUTPUT_DIRECTORY>/[keyword]_synthesis.md`), and give the user the path to it. 

### Error Handling

If you encounter `404 Not Found` or "element not visible" errors during the browser invocation:
- Keep in mind that Xiaohongshu may demand a login challenge. If the site pauses waiting for a login, instruct the user to verify the `playwright-cli` browser window and perform necessary authentication manually, then try the script again.

「知识管理」分类下的热门技能

数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。