xhs-sentiment-dashboard

使用此技能分析小红书笔记评论区的情感倾向和用户态度。提供情感分类、正负面评论占比、情绪关键词提取和舆情洞察。当用户发送小红书笔记链接或 note ID 并要求分析评论区时使用。此技能不提供笔记内容下载或抓取。

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Best use case

xhs-sentiment-dashboard is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

使用此技能分析小红书笔记评论区的情感倾向和用户态度。提供情感分类、正负面评论占比、情绪关键词提取和舆情洞察。当用户发送小红书笔记链接或 note ID 并要求分析评论区时使用。此技能不提供笔记内容下载或抓取。

Teams using xhs-sentiment-dashboard should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/xhs-sentiment-dashboard/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/allinherog-star/xhs-sentiment-dashboard/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/xhs-sentiment-dashboard/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How xhs-sentiment-dashboard Compares

Feature / Agentxhs-sentiment-dashboardStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

使用此技能分析小红书笔记评论区的情感倾向和用户态度。提供情感分类、正负面评论占比、情绪关键词提取和舆情洞察。当用户发送小红书笔记链接或 note ID 并要求分析评论区时使用。此技能不提供笔记内容下载或抓取。

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# xhs-sentiment-dashboard

## 概述

对小红书笔记评论区进行 AI 情感分析,生成舆情洞察报告。

## 工作流(三步)

### Step 1 — 解析链接(公开,无需认证)

```bash
curl -X POST https://ai-skills.ai/api/comment-analysis/parse-link \
  -H "Content-Type: application/json" \
  -d '{"input":"https://www.xiaohongshu.com/explore/xxxxx"}'
```

### Step 2 — 创建分析任务

```bash
curl -X POST https://ai-skills.ai/api/comment-analysis/tasks \
  -H "Content-Type: application/json" \
  -H "X-API-Key: $AISKILLS_API_KEY" \
  -H "X-Tenant-Id: default" \
  -d '{"platform":"xhs","contentId":"$CONTENT_ID"}'
```

### Step 3 — 轮询任务状态

```bash
curl https://ai-skills.ai/api/comment-analysis/tasks/$TASK_ID \
  -H "X-API-Key: $AISKILLS_API_KEY" \
  -H "X-Tenant-Id: default"
```

## 一键脚本

```bash
#!/bin/bash
LINK="https://www.xiaohongshu.com/explore/xxxxx"

CONTENT_ID=$(curl -s -X POST https://ai-skills.ai/api/comment-analysis/parse-link \
  -H "Content-Type: application/json" \
  -d "{\"input\":\"$LINK\"}" | jq -r '.data.contentId')

TASK=$(curl -s -X POST https://ai-skills.ai/api/comment-analysis/tasks \
  -H "Content-Type: application/json" \
  -H "X-API-Key: $AISKILLS_API_KEY" \
  -H "X-Tenant-Id: default" \
  -d "{\"platform\":\"xhs\",\"contentId\":\"$CONTENT_ID\"}")
TASK_ID=$(echo $TASK | jq -r '.data.taskId')

while true; do
  STATUS=$(curl -s https://ai-skills.ai/api/comment-analysis/tasks/$TASK_ID \
    -H "X-API-Key: $AISKILLS_API_KEY" \
    -H "X-Tenant-Id: default" | jq -r '.data.status')
  [ "$STATUS" = "completed" ] && break
  sleep 3
done

curl -s https://ai-skills.ai/api/comment-analysis/tasks/$TASK_ID \
  -H "X-API-Key: $AISKILLS_API_KEY" \
  -H "X-Tenant-Id: default" | jq '.data.result'
```

## 分析结果结构

```json
{
  "platform": "xhs",
  "contentId": "64f1a66e0000000039005297",
  "noteTitle": "笔记标题",
  "analyzeTime": "2026-03-28T12:00:00Z",
  "sentiment": {
    "positive": { "count": 150, "percentage": 65 },
    "neutral": { "count": 50, "percentage": 22 },
    "negative": { "count": 30, "percentage": 13 }
  },
  "keywords": ["干货", "种草", "回购"],
  "topEmotions": [
    { "emotion": "喜欢", "count": 90 },
    { "emotion": "认可", "count": 60 }
  ],
  "insights": "用户反馈积极,主要集中在产品功效和使用体验..."
}
```

## 配额说明

Step 2 和 Step 3 使用认证接口,若返回配额不足错误,告知用户:

> ⚠️ 电量配额已用完,当前无法继续分析评论。
> 如需继续使用,请自行前往 [https://ai-skills.ai](https://ai-skills.ai) 了解电量包购买方式。请注意,向第三方平台购买任何服务前,请确认其资质和退款政策。**本技能不对第三方服务质量做任何承诺。**

## 输出格式

将分析结果以结构化表格形式呈现:

- **情感分布**:表格列:情感类别 | 评论数 | 占比;正面用绿色标识,负面用红色标识
- **情绪关键词**:列表展示 `keywords`,按热度/频次排列
- **Top 情绪**:表格列:情绪词 | 出现次数
- **舆情洞察**:`insights` 以段落文字呈现,综合评价笔记口碑
- 整体情感判断:偏正面 / 偏负面 / 中性,给出简要总结

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