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social-media-analyzer

@alirezarezvani · 收录于 1 周前 · 上游提交 8 个月前

Analyzes social media campaign performance across platforms with engagement metrics, ROI calculations, and audience insights for data-driven marketing decisions

场景社媒复盘活动效果评估投放优化

适合你，如果你需要数据驱动地评估社交媒体活动效果。

/ 下载安装
social-media-analyzer.skill双击,或拖进 Claude 桌面版 / Cowork,即完成安装↓ .skill↓ .zip
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
Claude Code~/.claude/skills/(项目级 .claude/skills/)
Codex CLI~/.codex/skills/
Cursor自动读取上面两处目录
其他工具见其文档的「skills」目录;两个下载是同一份文件,只是名字不同
/ 通过 npx 安装 校验哈希
npx oh-my-skill add alirezarezvani/claude-code-skill-factory/social-media-analyzer
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- alirezarezvani/claude-code-skill-factory/social-media-analyzer
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify alirezarezvani/claude-code-skill-factory/social-media-analyzer
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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~2.5K含声明引用
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怎么用

技能原文 SKILL.md作者撰写 · MIT · ba18b31

Social Media Campaign Analyzer

This skill provides comprehensive analysis of social media campaign performance, helping marketing agencies deliver actionable insights to clients.

Capabilities
  • Multi-Platform Analysis: Track performance across Facebook, Instagram, Twitter, LinkedIn, TikTok
  • Engagement Metrics: Calculate engagement rate, reach, impressions, click-through rate
  • ROI Analysis: Measure cost per engagement, cost per click, return on ad spend
  • Audience Insights: Analyze demographics, peak engagement times, content performance
  • Trend Detection: Identify high-performing content types and posting patterns
  • Competitive Benchmarking: Compare performance against industry standards
Input Requirements

Campaign data including:

  • Platform metrics: Likes, comments, shares, saves, clicks
  • Reach data: Impressions, unique reach, follower growth
  • Cost data: Ad spend, campaign budget (for ROI calculations)
  • Content details: Post type (image, video, carousel), posting time, hashtags
  • Time period: Date range for analysis

Formats accepted:

  • JSON with structured campaign data
  • CSV exports from social media platforms
  • Text descriptions of key metrics
Output Formats

Results include:

  • Performance dashboard: Key metrics with trends
  • Engagement analysis: Best and worst performing posts
  • ROI breakdown: Cost efficiency metrics
  • Audience insights: Demographics and behavior patterns
  • Recommendations: Data-driven suggestions for optimization
  • Visual reports: Charts and graphs (Excel/PDF format)
How to Use

"Analyze this Facebook campaign data and calculate engagement metrics" "What's the ROI on this Instagram ad campaign with $500 spend and 2,000 clicks?" "Compare performance across all social platforms for the last month"

Scripts
  • calculate_metrics.py: Core calculation engine for all social media metrics
  • analyze_performance.py: Performance analysis and recommendation generation
Best Practices
  1. Ensure data completeness before analysis (missing metrics affect accuracy)
  2. Compare metrics within same time periods for fair comparisons
  3. Consider platform-specific benchmarks (Instagram engagement differs from LinkedIn)
  4. Account for organic vs. paid metrics separately
  5. Track metrics over time to identify trends
  6. Include context (seasonality, campaigns, events) when interpreting results
Limitations
  • Requires accurate data from social media platforms
  • Industry benchmarks are general guidelines and vary by niche
  • Historical data doesn't guarantee future performance
  • Organic reach calculations may vary by platform algorithm changes
  • Cannot access data directly from platforms (requires manual export or API integration)
  • Some platforms limit data availability (e.g., TikTok analytics for business accounts only)
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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