social-media-analyzer

social-media-analyzer is a skill for Claude Code, Codex from alirezarezvani/claude-code-skill-factory. It costs 28 tokens per session (598 once invoked), scanned A, original, MIT.

A tool for analyzing social media campaign data across platforms using engagement, audience, trend, and return-on-investment measures. It can use structured JSON, CSV exports, or text descriptions of campaign data.

In plain words
What is it for?
Use it to calculate engagement and advertising returns, examine audience patterns, find high-performing content, detect posting trends, and compare results with industry benchmarks.
Why use it?
It turns campaign figures into comparisons and insights about content, audiences, costs, and results.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to calculate engagement and advertising returns, examine audience patterns, find high-performing content, detect posting trends, and compare results with industry benchmarks.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/alirezarezvani/claude-code-skill-factory/social-media-analyzer
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add alirezarezvani/claude-code-skill-factory --skill social-media-analyzer
Clone the repo
git clone --depth 1 https://github.com/alirezarezvani/claude-code-skill-factory

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for social-media-analyzer

README.md
[![agentmods](https://agentmods.dev/badge/skills/alirezarezvani/claude-code-skill-factory/social-media-analyzer/github.svg)](https://agentmods.dev/skills/alirezarezvani/claude-code-skill-factory/social-media-analyzer)
Your own site
<a href="https://agentmods.dev/skills/alirezarezvani/claude-code-skill-factory/social-media-analyzer"><img src="https://agentmods.dev/badge/skills/alirezarezvani/claude-code-skill-factory/social-media-analyzer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for social-media-analyzer

Your own site · 80×15
<a href="https://agentmods.dev/skills/alirezarezvani/claude-code-skill-factory/social-media-analyzer"><img src="https://agentmods.dev/badge/skills/alirezarezvani/claude-code-skill-factory/social-media-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 598 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00028 $0.00598
Opus 5 $0.00014 $0.00299
Sonnet 5 $0.00006 $0.00120
Haiku 4.5 $0.00003 $0.00060

Measured 10d ago against content hash b7211136a8bb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

social-media-analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (analyze_performance.py, calculate_metrics.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

generated-skills/social-media-analyzer/SKILL.md · 71 lines

How it starts

The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

Read the full file on GitHub · 71 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 71 lines · 28 tokens per session scan A b7211136a8bb

Subscribe to this mod's changes

social-media-analyzer is a skill published in the GitHub repository alirezarezvani/claude-code-skill-factory (859 stars, last pushed 10mo ago), licensed MIT. It adds 28 tokens to every session and 598 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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