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code-archaeology

Map legacy code pipelines and document findings for academic projects.

127|22|Updated Feb 20, 2026
Search Tags:#documentation#data pipeline#code audit#code understanding#legacy code#project revival
One-click install
npx skills add https://github.com/flonat/claude-code-flonat --skill code-archaeology-flonat
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: code-archaeology
Source: https://github.com/flonat/claude-code-flonat/tree/main/skills/code-archaeology
Command: npx skills add https://github.com/flonat/claude-code-flonat --skill code-archaeology-flonat

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps researchers and developers systematically review and understand legacy code, data, and analysis files, making it easier to revive old projects, audit inherited code, or prepare for revisions.

Core Features & Use Cases

  • Exploration: Identifies existing files, directory structure, and modification dates.
  • Pipeline Understanding: Maps out main scripts, their execution order, data inputs, and outputs.
  • Documentation: Assists in creating or updating READMEs and documenting data flows.
  • Safety Establishment: Guides the creation of a legacy/ folder for original files and sets up version control.
  • Use Case: You're returning to a complex analysis project after a year-long break. This Skill will help you quickly re-familiarize yourself with the codebase, understand how the data was processed, and ensure everything is safely backed up before you start making changes.

Quick Start

Use the code-archaeology skill to explore the current project directory and document its structure and main scripts.

Frequently Asked Questions about code-archaeology

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I systematically review and understand legacy code for a project revival?▼

To review legacy code for project revival, systematically explore the directory structure, map data pipelines, document execution order, and establish safety protocols by copying original files to a legacy folder.

What is the best way to map data pipelines in inherited academic research code?▼

Mapping data pipelines in inherited code involves identifying main scripts, determining their execution order, and tracing data inputs and outputs to document the complete data flow.

Can I use this approach to audit code and prepare for R&R submissions?▼

Yes, you can audit inherited code and prepare for R&R submissions by exploring existing files, updating documentation like READMEs, and mapping out data flows to ensure research reproducibility.

How do I safely backup original analysis files before modifying an old project?▼

To safely backup original analysis files before modifying an old project, establish safety protocols by creating a legacy folder and copying the original files there before starting any version control changes.

What are the limitations of using a code audit approach for academic researchers?▼

The code audit approach focuses strictly on systematically reviewing and understanding legacy code, data, and analysis files for academic researchers; it does not execute code or automatically fix underlying script errors.

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