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data-forensics

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Authenticate raw data with forensic tests.

Data & Analytics#data-integrity#sprite#data-validation#data-forensics#benford#grim
AuthorTerryFYL
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Raw data authenticity is critical for credible analyses. This Skill provides a structured, multipath workflow to detect data fabrication, inconsistencies, and suspicious patterns before downstream analysis or manuscript generation.

Core Features & Use Cases

  • Seven-forensic tests: GRIM, SPRITE, Benford's Law, Terminal Digit, Variance Uniformity, Distribution Plausibility, and Duplicate Pattern checks to flag potential data issues.
  • Risk-aware reporting: Produces a forensics_report.md with a flag-based risk rating (GREEN/YELLOW/RED) and actionable recommendations.
  • Pipeline integration: Seamlessly slots into data-profiler pipelines (Step 1.5) and can operate as an independent risk-check during client intake.

Quick Start

Provide the raw data file path (CSV/Excel/SPSS/Stata) to run the seven-forensic tests and generate the forensics_report.md with a risk rating.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

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Please help me install this Skill:
Name: data-forensics
Download link: https://github.com/TerryFYL/ai-research-army/archive/main.zip#data-forensics

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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