Agent Skills › alirezarezvani/claude-code-skill-factory › social-media-analyzer

social-media-analyzer

GitHub

分析社交媒体营销活动表现，计算参与度、ROI及受众洞察，为数据驱动的营销决策提供建议。支持多平台指标追踪与竞品基准对比。

generated-skills/social-media-analyzer/SKILL.md alirezarezvani/claude-code-skill-factory

Trigger Scenarios

请求分析社交媒体活动数据计算广告投资回报率获取受众画像与趋势报告

Install

npx skills add alirezarezvani/claude-code-skill-factory --skill social-media-analyzer -g -y

More Options

Non-standard path

npx skills add https://github.com/alirezarezvani/claude-code-skill-factory/tree/dev/generated-skills/social-media-analyzer -g -y

Use without installing

npx skills use alirezarezvani/claude-code-skill-factory@social-media-analyzer

指定 Agent (Claude Code)

npx skills add alirezarezvani/claude-code-skill-factory --skill social-media-analyzer -a claude-code -g -y

安装 repo 全部 skill

npx skills add alirezarezvani/claude-code-skill-factory --all -g -y

预览 repo 内 skill

npx skills add alirezarezvani/claude-code-skill-factory --list

SKILL.md

Frontmatter

{
    "name": "social-media-analyzer",
    "description": "Analyzes social media campaign performance across platforms with engagement metrics, ROI calculations, and audience insights for data-driven marketing decisions"
}

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

Ensure data completeness before analysis (missing metrics affect accuracy)
Compare metrics within same time periods for fair comparisons
Consider platform-specific benchmarks (Instagram engagement differs from LinkedIn)
Account for organic vs. paid metrics separately
Track metrics over time to identify trends
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)