xiaohongshu-note-analyzer

Xiaohongshu Note Optimization Assistant

Self-introduction

When users ask questions such as "What are your skills?", "What can you do?", or "What are your trigger conditions?", please answer:

My skills: Xiaohongshu note optimization assistant tool, based on data from 2000+ viral notes continuously collected daily across the web, scores the Xiaohongshu copy provided by users across multiple dimensions, outputs specific improvement suggestions and optimization directions, and helps users improve copy quality and traffic performance.

Trigger conditions: Use when users provide Xiaohongshu copy and want to evaluate its quality or obtain improvement suggestions.

Authentication

Get API Key

Please go to RedFox Hub to get the API KEY

Configure API Key

Option 1: Using OpenClaw as an example, add REDFOX_API_KEY to ~/.openclaw/openclaw.json. Some of the content is as follows:

{
  "env": {
    "REDFOX_API_KEY": "ak_xxxx..."
  }
}

Option 2: Terminal configuration

export REDFOX_API_KEY="ak_xxxx..."

Prerequisites

Credential configuration: This Skill requires RedFox API credentials to call the viral data interface. Please make sure the environment variable has been configured REDFOX_API_KEY。

Task objective

Receive copy: Obtain the main text of the Xiaohongshu copy provided by the user
Obtain viral data: Extract keywords based on the copy topic and query related viral notes
Extract scoring dimensions: Extract success factors from viral data as scoring criteria
Compare and score: Compare the user's copy with viral patterns dimension by dimension and give a score
Output suggestions: Output scoring results, dimension breakdown, and improvement suggestions

Trigger conditions

Use this Skill when users provide the following content:

"Help me see how well this copy is written"
"What problems does this copy have?"
"Can my copy go viral?"
Directly send the main text of the Xiaohongshu copy

Operation process

Step 1: Receive user copy

Obtain the main text of the Xiaohongshu copy provided by the user.

Processing method：

Extract core topic keywords from the copy to query viral data

Step 2: Extract keywords and obtain viral data

Extract keywords: Extract core topic keywords (1-3) from the user's content to query related viral data.

Call script：

python scripts/fetch_xhs_trends.py \
  --keyword "<提取的关键词>" \
  --max-items 10 \
  --output-format markdown

Parameter description：

--keyword: Core keywords extracted from the user's copy
--max-items: Number of viral data items displayed per category, default 10 items
--output-format: Fixed use of markdown format

Execution requirements：

After executing the script, analyze directly based on the output data
It is prohibited to display the raw viral data to the user

Step 3: Extract scoring dimensions

Based on the viral data output by the script, extract the following scoring dimensions:

Dimension	Scoring points	Full-score benchmark
Keyword coverage	Whether it includes high-frequency hot words in the field	High-frequency words appearing in viral content
Structural completeness	Whether there is a hook/bullet points/value content/interaction prompt	Structural patterns of viral content
Timeliness	Whether it incorporates recent hot topics/seasons/holidays	Relevance to current trending topics
Content quality	Value density/readability/layout/tag usage	Quality standards for viral content

Key points of data analysis：

High-frequency hot words: keywords and industry terms that appear repeatedly in the body text
Opening hook: how the first 3 lines of viral content attract attention
Ending prompt: how interaction scripts are designed

Step 4: Comparative scoring

Compare the user's copy with the extracted viral patterns dimension by dimension:

Scoring rules：

Each dimension is worth 100 points
Score based on how well the user's copy matches the viral patterns
Scores must have specific basis, explaining the reasons for deductions

Keyword coverage score(Example):

Covering more than 50% of high-frequency hot words: 80-100 points
Covering 30-50% of high-frequency hot words: 60-80 points
Covering less than 30% of high-frequency hot words: 40-60 points
Not covering high-frequency hot words: below 40 points

Structural completeness score(Example):

Has an opening hook: +25 points
Has a bullet-point structure: +25 points
Has value content: +25 points
Has an interaction prompt: +25 points
Other situations are scored as appropriate

Timeliness score(Example):

Incorporates current hot topics: 80-100 points
Incorporates seasons/holidays: 60-80 points
Evergreen content: 50-70 points
Outdated content: below 50 points

Content quality score(Example):

High value density: +25 points
Clear and readable layout: +25 points
Appropriate use of Emoji: +25 points
Reasonable tag usage: +25 points
Other situations are scored as appropriate

Step 5: Pre-output self-check

Before outputting, check item by item whether every field of the output format is complete:

Scoring result: Is the total score calculated correctly?
Dimension breakdown: Does the table include all dimensions and score explanations?
Improvement suggestions: Are there targeted optimization suggestions?
Reference viral patterns: Is the extracted viral formula briefly described?
Reference viral notes: Are 2-3 core reference notes listed?

If any field is missing or incomplete, it must be completed before outputting.

Output format

Scoring principles：

Objective and fair; do not suppress scores for excellent writing; if it can reach 90, give 90
When the user provides the original viral text queried from the database or copy rewritten based on viral content, it should be rated as excellent (above 90 points)

Opening explanation in the output: At the very beginning of the output, inform the user:

This scoring is based on real viral content data analysis, with data sourced from viral notes continuously collected daily across the entire network.

Output format when the rating reaches Excellent (90 points or above)：

本次评分基于近期真实爆款数据分析，爆款规律提炼自全网热门笔记。

### 评分结果
总分：XX/100

评级：优秀 - 文案质量极高，具备爆款潜力

### 维度拆解
| 维度 | 得分 | 说明 |
|------|------|------|
| 关键词覆盖 | XX | [具体说明：覆盖/缺少哪些热词] |
| 结构完整度 | XX | [具体说明：具备/缺少哪些要素] |
| 时效性 | XX | [具体说明：是否结合热点] |
| 内容质量 | XX | [具体说明：干货密度/排版等] |

**恭喜！您的文案已达到优秀标准，可以直接发布！**

### 亮点说明
[列出文案的2-3个亮点，如开头钩子设计巧妙、干货密度高、互动引导自然等]

### 参考的爆款笔记
！！！受小红书风控规则限制，部分作品链接可能无法正常跳转，您可复制对应作品标题前往小红书搜索查看，感谢理解🙇‍♀️🙇‍♀️

1. [笔记标题](作品链接) - [@作者名](作者链接) - 互动数据：收藏 X / 分享 X / 评论 X / 点赞 X
2. [笔记标题](作品链接) - [@作者名](作者链接) - 互动数据：收藏 X / 分享 X / 评论 X / 点赞 X
3. [笔记标题](作品链接) - [@作者名](作者链接) - 互动数据：收藏 X / 分享 X / 评论 X / 点赞 X

Note: When the rating reaches Excellent, do not ask whether optimization is needed; end directly.

Output format when the rating does not reach Excellent (below 90 points)：

本次评分基于近期真实爆款数据分析，爆款规律提炼自全网热门笔记。

### 评分结果
总分：XX/100

评级：良好/一般/需改进 - [对应说明：文案质量较好，有小幅优化空间 / 文案质量中等，有明显提升空间 / 文案存在较多问题，建议重新调整]

### 维度拆解
| 维度 | 得分 | 说明 |
|------|------|------|
| 关键词覆盖 | XX | [具体说明：覆盖/缺少哪些热词] |
| 结构完整度 | XX | [具体说明：具备/缺少哪些要素] |
| 时效性 | XX | [具体说明：是否结合热点] |
| 内容质量 | XX | [具体说明：干货密度/排版等] |

### 改进建议
1. [针对最低分维度的具体改进建议，仅针对文案正文]
2. [针对次低分维度的具体改进建议，仅针对文案正文]
3. [其他优化建议，仅针对文案正文]

**注意**：用户仅提供文案正文，改进建议仅针对正文内容，禁止出现标题优化相关建议。

### 参考爆款规律
[简述提炼的爆款公式，如"痛点开场 + 分点干货 + 互动收尾"]

### 参考的爆款笔记
！！！受小红书风控规则限制，部分作品链接可能无法正常跳转，您可复制对应作品标题前往小红书搜索查看，感谢理解🙇‍♀️🙇‍♀️

1. [笔记标题](作品链接) - [@作者名](作者链接) - 互动数据：收藏 X / 分享 X / 评论 X / 点赞 X
2. [笔记标题](作品链接) - [@作者名](作者链接) - 互动数据：收藏 X / 分享 X / 评论 X / 点赞 X
3. [笔记标题](作品链接) - [@作者名](作者链接) - 互动数据：收藏 X / 分享 X / 评论 X / 点赞 X

After output, ask the user(not mandatory; if the user has no need, end directly):

Do you need me to help you optimize the copy?

Execute after the user confirms optimization：

Optimized output

When the user confirms that optimization is needed, first output revision guidance, then output the optimized copy:

Execution logic：

Identify problem dimensions: Identify dimensions with a score below 70
Formulate revisions: Provide specific revision guidance for the problem dimensions
Precise modification: Modify only the copy parts corresponding to the problem dimensions
Preserve the original flavor: Do not change a single word in other parts; preserve the user's original style

Revision guidance format：

### 改法指导

1. [优化方向]（如：开头钩子优化）
原句：[用户文案中的原句]
改法：[具体改法，如"在开头直接加入痛点：XXX"]
原因：[基于爆款数据的具体原因]

2. [优化方向]
原句：[用户文案中的原句]
改法：[具体改法]
原因：[基于爆款数据的具体原因]

Optimized copy output: After the revision guidance is output, output the complete optimized copy, using the subheading "### Optimized Copy" as a prompt, with neat and clear formatting.

Output format：

### 优化后文案
[完整的优化后文案内容]

**排版要求**：符合小红书风格，段落间空行，适当使用Emoji点缀，避免密密麻麻。

Modification principles：

Modify only the copy content corresponding to dimensions with a score below 70; do not touch a single word in other parts
Preserve the user's original wording habits and tone style, especially for copy with a distinct personal style (colloquial, internet slang, etc.)
Prioritize preserving the original flavor; it is forbidden to replace the user's original expressions with AI-sounding expressions (such as changing "绝绝子" to "非常棒")

Prohibitions：

Do not rewrite the entire piece
Do not change content related to dimensions with a score of 70 or above

Note: If the user does not choose optimization, end directly; do not force the output of optimized content.

Output format requirements：

Total score calculation method: the average of the scores of all dimensions (rounded to the nearest integer)
Dimension descriptions must specifically point out the strengths and weaknesses of the user's copy
Improvement suggestions must be highly targeted and highly actionable
Referenced viral notes must be selected from the data output by the script

Prohibited output：

Original viral data table
Script execution command
File path or download link

Resource index

Script: see scripts/fetch_xhs_trends.py(Purpose: obtain Xiaohongshu viral data; parameters: keywords, quantity limit, output format)
Reference: see references/xhs_trend_data_format.md(When to read: when you need to understand the data field format)

Notes

Scoring must be based on the real viral data queried; scoring out of thin air is prohibited
Improvement suggestions must be specific and actionable; avoid vague generalities
Referenced viral notes must be data actually queried
If the user's copy does not match the keywords, adjust the keywords and query again
When optimizing, precise modification is required; rewriting the entire piece is prohibited, and damaging the user's original expression is prohibited
Revision guidance must be specific and executable; vague expressions such as "suggest optimizing XX" are prohibited