audio-processing
Use when processing audio for Xiaohongshu content, editing voiceovers, improving sound…
Use when conducting deep analytics on Xiaohongshu accounts, tracking content performance trends, researching influencer data, monitoring category growth, or making strategic decisions with comprehensive social media analytics
$ npx -y skills add vivy-yi/xiaohongshu-skills --skill xinhong-data --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/xinhong-dataContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when conducting deep analytics on Xiaohongshu accounts, tracking content performance trends, researching influencer data, monitoring category growth, or making strategic decisions with comprehensive social media analytics
name: xinhong-data description: Use when conducting deep analytics on Xiaohongshu accounts, tracking content performance trends, researching influencer data, monitoring category growth, or making strategic decisions with comprehensive social media analytics
Xinhong Data is a professional analytics platform specifically designed for Xiaohongshu, providing deep insights into account growth, content performance, influencer partnerships, industry trends, and competitive intelligence with granular data visualization and reporting capabilities for brands, agencies, and serious creators.
**Use when**:
**Do NOT use when**:
**Before** (surface-level analytics):
❌ "Basic metrics only (likes, followers)" ❌ "No trend analysis over time" ❌ "Shallow competitor insights" ❌ "Guessing content strategy" ❌ "Blind to industry shifts"
**After** (deep data intelligence):
✅ "Complete account health dashboard" ✅ "Trend analysis with actionable insights" ✅ "Deep competitor benchmarking" ✅ "Data-driven content optimization" ✅ "Industry trend forecasting"
**5 Analytics Dimensions**: 1. **Account Growth Analysis** - Comprehensive growth tracking 2. **Content Performance Deep Dive** - Detailed content metrics 3. **Audience Insights** - Demographics and behavior 4. **Competitor Benchmarking** - Strategic comparison 5. **Industry Trend Analysis** - Market intelligence
| Analysis Type | Data Depth | Update Frequency | Best For | |--------------|------------|------------------|----------| | **Account Audit** | Comprehensive | Monthly | Strategy reviews | | **Content Analysis** | Post-level | Real-time | Content optimization | | **Audience Study** | Demographic | Weekly | Targeting refinement | | **Competitor Intel** | Comparative | Bi-weekly | Strategic planning | | **Trend Forecast** | Industry-wide | Monthly | Opportunity spotting |
**Comprehensive Performance Review**:
Account Audit Framework: 1. Growth Trajectory Analysis Long-Term Performance Tracking: Growth Metrics (90-Day View): Follower Growth: - Starting count (Day 1) - Ending count (Day 90) - Net growth - Growth rate percentage - Daily average growth - Growth velocity (accelerating/decelerating) Growth Velocity: - Week 1-4: Growth rate - Week 5-8: Growth rate - Week 9-12: Growth rate - Trend identification (acceleration/stagnation) Benchmarking: - vs. Previous period (MoM, YoY) - vs. Category average - vs. Competitors (similar size) - Percentile ranking Audit Example: "Account Growth Audit (Q1 2026): 90-Day Period: Jan 1 - Mar 31 Follower Metrics: - Starting: 8,500 - Ending: 12,750 - Net growth: +4,250 - Growth rate: +50% (excellent) - Daily average: +47.2 followers/day Velocity Analysis: January: +1,200 (14% growth) February: +1,550 (18% growth from Jan) March: +1,500 (13% growth from Feb) Trend: Accelerating through Feb, stabilizing in Mar Benchmarking: - Category average: 8% quarterly growth - Your performance: 50% (6.25x category!) - Competitor avg (similar size): 12% - Your percentile: Top 5% in category Growth Drivers Identified: - Educational carousels (40% of growth) - Live stream appearances (30% of growth) - Influencer shoutouts (20% of growth) - Viral content (10% of growth) Recommendations: - Double down on educational content (primary driver) - Increase live stream frequency (high ROI) - Nurture influencer relationships (sustainable growth) - Test more viral content formats" 2. Engagement Quality Assessment Beyond Surface Metrics: Engagement Breakdown: Component Analysis: - Likes: Passive engagement baseline - Comments: Active engagement indicator - Saves: Value indicator (future reference) - Shares: Viral potential measure - Follows from post: Conversion metric Quality Metrics: Comment Quality: - Avg comment length (characters) - Question vs. statement ratio - @mentions (conversation depth) - Emoji usage (sentiment expression) - Thread depth (reply chains) Sentiment Analysis: - Positive sentiment (%) - Negative sentiment (%) - Neutral sentiment (%) - Brand mentions sentiment - Product feedback sentiment Engagement Health Report: "Engagement Quality Audit (March 2026): Overall Engagement Rate: 8.2% (above 5% category avg) Component Breakdown: - Likes: 68% of total engagement - Comments: 15% (high! good conversation) - Saves: 14% (excellent! content valued) - Shares: 3% (opportunity to improve) Comment Quality Analysis: Sample: 500 comments analyzed Avg length: 18 characters (substantial) Questions: 35% (high engagement!) @mentions: 12% (community interaction) Emoji usage: 45% (expressive) Thread depth: 2.3 avg replies (good discussion) Sentiment Breakdown: - Positive: 78% (excellent) - Neutral: 19% - Negative: 3% (low, manageable) Top Engagement Drivers: 1. Educational carousels: 12% engagement, 25% saves 2. Before/after posts: 10% engagement, 18% shares 3. Personal stories: 9% engagement, 22% comments 4. Tutorials: 8.5% engagement, 15% saves 5. Product demos: 7% engagement, 10% comments Underperforming: 1. Generic quotes: 4% engagement, 3% saves 2. Pure promotion: 4.5% engagement, 2% shares 3. Reposted content: 5% eng
版本: v3.0 Complete Edition 更新: 2025-01-22 状态: ✅ 完整 (139个技能)
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