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alirezarezvani

Social Media Analyzer

by Alireza Rezvani · GitHub ↗ · v2.1.1 · MIT-0
cross-platform ⚠ suspicious
1977
Downloads
1
Stars
19
Active Installs
2
Versions
Install in OpenClaw
/install social-media-analyzer
Description
Social media campaign analysis and performance tracking. Calculates engagement rates, ROI, and benchmarks across platforms. Use for analyzing social media pe...
Usage Guidance
This skill is not showing malicious behavior, but it has implementation/documentation mismatches that can produce incorrect metrics. Before trusting results: (1) Run the included scripts locally with the provided assets/sample_input.json and compare to assets/expected_output.json to reproduce differences. (2) Inspect and fix calculate_metrics.calculate_campaign_metrics: it currently sums likes+comments+shares but omits saves, while per-post engagement includes saves — add saves to total_engagements to align totals. (3) Decide whether ROI should use per-action values from SKILL.md (likes $0.50, comments $2, etc.) or a flat avg_value_per_engagement; if using per-action values, change calculate_roi_metrics to compute estimated_value = likes*$0.50 + comments*$2 + ... for accurate ROAS. (4) Verify benchmark units are consistent (both docs and code use percent values) and that string formatting doesn't mislead (e.g., numeric values vs percent strings). (5) Because the skill runs Python code, only run it on non-sensitive data until you audit it; no external network calls are present, but you should still review the code before executing in a sensitive environment. If you want, I can produce the concrete code patches to correct the omissions and align ROI calculation with the documented per-action values.
Capability Analysis
Type: OpenClaw Skill Name: social-media-analyzer Version: 2.1.1 The skill bundle is a legitimate tool for social media campaign analysis and ROI calculation. The Python scripts (scripts/calculate_metrics.py and scripts/analyze_performance.py) contain standard data processing logic with no evidence of network access, file system manipulation, or shell execution. The instructions in SKILL.md are well-defined and strictly focused on the stated purpose of performance tracking and benchmarking.
Capability Assessment
Purpose & Capability
The name/description match the provided artifacts: SKILL.md, example input/output, benchmark reference, and two Python scripts that calculate metrics, ROI, and recommendations. The code and instructions are consistent with a social media analytics tool — no unrelated binaries, credentials, or external services are requested.
Instruction Scope
SKILL.md instructs running the included Python scripts and defines metrics and value tables. However, the runtime behavior diverges from the documentation and expected output: calculate_engagement_rate (per-post) includes saves in engagements, but calculate_campaign_metrics (campaign totals) omits saves when summing total_engagements, causing avg_engagement_rate and ROI to be computed from inconsistent totals. Also, SKILL.md lists per-action monetary values but scripts use a single avg_value_per_engagement = 2.50 rather than computing value from per-action values. These inconsistencies will produce different numbers than the documentation/expected_output and may silently mislead users.
Install Mechanism
No install spec is provided (instruction-only with bundled scripts). Nothing is downloaded or installed automatically; the risk surface is limited to running the included Python code locally.
Credentials
The skill requests no environment variables, no credentials, and no config paths. The Python scripts do not reference environment secrets or network endpoints; they operate on provided JSON input only.
Persistence & Privilege
The skill does not request persistent/autonomous privileges (always: false). It does not modify other skills or system-wide settings based on the provided files.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install social-media-analyzer
  3. After installation, invoke the skill by name or use /social-media-analyzer
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v2.1.1
v2.1.1: optimization, reference splits
v1.0.0
- Initial release of the Social Media Analyzer skill. - Analyze social media campaign performance with engagement metrics, ROI calculations, and cross-platform benchmarks. - Calculate engagement rate, CTR, reach rate, and campaign ROI using customizable metrics. - Compare campaign results against industry-standard benchmarks for Instagram, Facebook, Twitter/X, LinkedIn, and TikTok. - Provides clear data validation, actionable recommendations, and sample input/output for easy reference. - Includes tools and scripts for automating analysis and metric calculations.
Metadata
Slug social-media-analyzer
Version 2.1.1
License MIT-0
All-time Installs 19
Active Installs 19
Total Versions 2
Frequently Asked Questions

What is Social Media Analyzer?

Social media campaign analysis and performance tracking. Calculates engagement rates, ROI, and benchmarks across platforms. Use for analyzing social media pe... It is an AI Agent Skill for Claude Code / OpenClaw, with 1977 downloads so far.

How do I install Social Media Analyzer?

Run "/install social-media-analyzer" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Social Media Analyzer free?

Yes, Social Media Analyzer is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Social Media Analyzer support?

Social Media Analyzer is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Social Media Analyzer?

It is built and maintained by Alireza Rezvani (@alirezarezvani); the current version is v2.1.1.

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