xiaohongshu-note-analyzer▌
softbread/xiaohongshu-doctor · updated May 2, 2026
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Comprehensive analysis of Xiaohongshu notes covering keyword optimization, title appeal, content risks, and engagement potential.
- ›Analyzes six dimensions: keyword strategy and density, headline/opening paragraph appeal, sensitive content risk detection, commercial authenticity scoring, discussion triggers, and content structure
- ›Provides risk assessment across medical/health, financial, political, false advertising, and low-taste content categories with specific violation detection
- ›De
小红书笔记分析器 (XiaoHongShu Note Analyzer)
对小红书笔记进行全方位分析,提供优化建议,提升内容质量和曝光率。
分析维度
- 关键词分析 — 搜索热度、关键词布局、标签优化
- 标题/首段吸引力 — 爆款标题元素、首图文案
- 敏感内容风险 — 违规词检测、限流风险评估
- 商业化程度 — 软广硬广识别、自然度评分
- 互动触发潜力 — 讨论点、分享动机、收藏价值
- 内容结构 — 排版、emoji使用、段落节奏
分析流程
1. 提取笔记内容 → 标题、正文、标签、图片描述
2. 关键词分析 → 核心词、长尾词、布局检查
3. 敏感词扫描 → 违规风险、限流风险
4. 商业化评估 → 广告痕迹、自然度
5. 互动潜力评估 → 讨论点、情感共鸣
6. 生成优化建议 → 具体修改方案
1. 关键词分析
检查要点
| 维度 | 优秀 | 待改进 |
|---|---|---|
| 核心关键词 | 标题+首段+正文+标签都包含 | 仅出现1-2处 |
| 长尾关键词 | 3-5个相关长尾词自然分布 | 无长尾词或堆砌 |
| 标签数量 | 5-10个相关标签 | <3个或>15个 |
| 关键词密度 | 2-3%自然出现 | <1%或>5%堆砌 |
关键词布局公式
标题: 必含核心关键词 + 吸引词
首段(前50字): 核心关键词 + 痛点/好奇点
正文: 长尾关键词自然分布
标签: #核心词 #长尾词 #场景词 #人群词
详见 references/keyword-strategy.md
2. 标题/首段吸引力
爆款标题公式
| 类型 | 公式 | 示例 |
|---|---|---|
| 数字型 | 数字+关键词+结果 | "5个技巧让你月瘦10斤" |
| 痛点型 | 痛点+解决方案 | "毛孔粗大?这个方法亲测有效" |
| 好奇型 | 悬念+关键词 | "闺蜜问我怎么突然变白的..." |
| 对比型 | Before/After | "用了这个精华,同事都问我怎么了" |
| 权威型 | 身份+干货 | "皮肤科医生自用的5款防晒" |
| 情绪型 | 强烈情绪词 | "后悔没早点知道!这个神器太绝了" |
首段黄金50字
首段必须包含:
- ✅ 核心关键词
- ✅ 痛点/需求点
- ✅ 吸引继续阅读的钩子
- ✅ 与封面图呼应
详见 references/title-formulas.md
3. 敏感内容风险评估
风险等级
| 等级 | 说明 | 后果 |
|---|---|---|
| 🔴 高危 | 明确违规词 | 删帖/封号 |
| 🟠 中危 | 灰色地带词 | 限流/不推荐 |
| 🟡 低危 | 可能触发审核 | 延迟发布 |
| 🟢 安全 | 无敏感内容 | 正常推荐 |
常见敏感类别
- 医疗健康类 — 疾病名称、药品、治疗效果承诺
- 金融理财类 — 收益承诺、投资建议、借贷
- 政治敏感类 — 时政、领导人、敏感事件
- 虚假宣传类 — 最、第一、100%、绝对
- 引流违规类 — 微信号、外链、二维码暗示
- 低俗擦边类 — 性暗示、身材过度暴露
详见 references/sensitive-words.md
4. 商业化程度评估
自然度评分标准
| 分数 | 描述 | 特征 |
|---|---|---|
| 9-10 | 纯分享 | 无品牌露出,真实体验 |
| 7-8 | 软植入 | 自然提及品牌,不刻意 |
| 5-6 | 明显软广 | 品牌多次出现,有推荐意图 |
| 3-4 | 硬广 | 明显推销,价格引导 |
| 1-2 | 纯广告 | 通篇产品介绍,无真实体验 |
降低商业感技巧
- ✅ 先讲痛点/故事,后引出产品
- ✅ 提及缺点(真实感)
- ✅ 对比其他产品(客观感)
- ✅ 强调个人体验而非产品功能
- ❌ 避免价格、购买链接、促销信息
- ❌ 避免品牌名在标题
5. 互动触发潜力
讨论触发点
| 类型 | 方法 | 示例 |
|---|---|---|
| 提问式 | 结尾抛出问题 | "你们觉得哪个颜色更好看?" |
| 争议式 | 轻度争议观点 | "我觉得XX比XX好用,有人同意吗?" |
| 求助式 | 请求建议 | "姐妹们帮我看看选哪个!" |
| 共鸣式 | 引发情感共鸣 | "有没有和我一样的..." |
| 抽奖式 | 互动福利 | "评论区抽3位送同款" |
分享动机触发
用户分享笔记的原因:
- 实用价值 — 干货教程、省钱攻略
- 社交货币 — 显得有品味/见识
- 情感共鸣 — "说出了我的心声"
- 收藏备用 — 清单、合集、测评
收藏价值评估
高收藏内容特征:
- ✅ 清单/合集形式
- ✅ 步骤教程
- ✅ 对比测评
- ✅ 省钱/避坑指南
- ✅ 信息密度高
输出格式
# 小红书笔记分析报告
## 📊 综合评分: X/10
## 1️⃣ 关键词分析
- **核心关键词**: [识别的关键词]
- **关键词布局**: ✅/❌ [评价]
- **标签优化**: [建议]
## 2️⃣ 标题/首段评估
- **标题类型**: [数字型/痛点型/...]
- **吸引力评分**: X/10
- **优化建议**: [具体建议]
## 3️⃣ 敏感内容风险
- **风险等级**: 🟢/🟡/🟠/🔴
- **检测到的敏感词**: [列表]
- **修改建议**: [具体建议]
## 4️⃣ 商业化程度
- **自然度评分**: X/10
- **商业痕迹**: [分析]
- **降低商业感建议**: [具体建议]
## 5️⃣ 互动潜力
- **讨论触发点**: ✅/❌
- **分享动机**: [分析]
- **收藏价值**: X/10
## 6️⃣ 优化后版本
[提供优化后的标题和首段]
## 📝 修改优先级
1. [最重要的修改]
2. [次重要的修改]
3. [可选优化]
分析示例
详见 references/analysis-examples.md
How to use xiaohongshu-note-analyzer on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add xiaohongshu-note-analyzer
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches xiaohongshu-note-analyzer from GitHub repository softbread/xiaohongshu-doctor and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate xiaohongshu-note-analyzer. Access the skill through slash commands (e.g., /xiaohongshu-note-analyzer) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
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Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★49 reviews- ★★★★★Meera Reddy· Dec 28, 2024
Solid pick for teams standardizing on skills: xiaohongshu-note-analyzer is focused, and the summary matches what you get after install.
- ★★★★★Mia Khan· Dec 24, 2024
xiaohongshu-note-analyzer has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Ganesh Mohane· Dec 16, 2024
xiaohongshu-note-analyzer has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★William Patel· Dec 16, 2024
We added xiaohongshu-note-analyzer from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Ama Li· Dec 4, 2024
xiaohongshu-note-analyzer reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Yash Thakker· Nov 27, 2024
Solid pick for teams standardizing on skills: xiaohongshu-note-analyzer is focused, and the summary matches what you get after install.
- ★★★★★Kwame Abebe· Nov 23, 2024
xiaohongshu-note-analyzer has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Min Agarwal· Nov 15, 2024
xiaohongshu-note-analyzer reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Meera Sethi· Nov 11, 2024
xiaohongshu-note-analyzer is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Sakshi Patil· Nov 7, 2024
xiaohongshu-note-analyzer reduced setup friction for our internal harness; good balance of opinion and flexibility.
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