agentsclimarketplace

Social media analyzer

Skill bg-szy/TOP-SKILLS/skills/marketplace/social-media-analyzer

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Install
npx -y skills add bg-szy/TOP-SKILLS --skill social-media-analyzer

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What its author says it does

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

SKILL.md

3.0 KB, 551 tokens by cl100k_base, as published. Nobody here has run it

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)

Gives 0 of the 12 instructions most social media skills give in 551 tokens

Counted across 489 of the 492 authors here whose files we hold, read 2026-08-06

  • build content around three to five pillarsin 24 of 489, across 12 files
  • read product marketing context before asking questionsin 23 of 489, across 13 files
  • respond to all comments on your postsin 21 of 489, across 9 files
  • adapt tone and structure per platformin 18 of 489, across 8 files
  • adapt content for each platformin 15 of 489, across 10 files
  • use the output flag to specify an output directoryin 14 of 489, across 4 files
  • Generate output logo images with white backgroundin 13 of 489, across 4 files
  • Fix failing generation scripts directlyin 13 of 489, across 4 files
  • ask user about html preview after logo generationin 12 of 489, across 3 files
  • run the download script with a URLin 12 of 489, across 3 files
  • implement exponential backoff for 429 responsesin 12 of 489, across 3 files
  • include a single clear call to actionin 12 of 489, across 9 files

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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