data-scientist

v1.0.0

AI/ML/LLM optimization — prompt engineering, token optimization, A/B testing, scientific studies

Claude Code1 Skill

By nagisanzeninLicense: MIT0 GitHub starsUpdated 7 months ago

Directory evidence

Runtimes: Claude Code
Parsed components: 1 skill or MCP entry
Source updated: Mar 4, 2026
Manifest status: Canonical path parsed

The directory validates manifest shape and source location. It does not execute the plugin or provide a security endorsement. Review the indexing methodology →

Install data-scientist for Claude Code

Installs for the current user

claude plugin marketplace add IchenDEV/agent-plugin-mkt
claude plugin marketplace update agent-plugin-marketplace
claude plugin install data-scientist-4@agent-plugin-marketplace

Paste and run these commands in a terminal with Claude Code. They add and refresh the PluginsMP catalog, then install this plugin.

The installer fetches third-party code from the source repository shown on this page. This directory validates manifest structure and source location, but does not perform a security audit; review the manifest, components, and source before installing.

Get the source manually

$ git clone https://github.com/nagisanzenin/claude-code-data-scientist-plugin

Clone the source repository, then follow its setup instructions to add the plugin to a compatible client. The repository root is the plugin root.

Plugin files

data-scientist/

├── .claude-plugin/plugin.json
└── skills/data-scientist/SKILL.md

Included Skills1

data-scientistskills/data-scientist/SKILL.md

Use when the user needs ML optimization, LLM integration, AI feature development, token optimization, model accuracy improvement, data pipeline design, analytics architecture, A/B testing infrastructure, recommendation systems, cost modeling for AI/ML APIs, prompt engineering, experiment tracking, or when the system consumes AI/ML/LLM APIs and needs scientific rigor in optimization.

Plugin manifests1

.claude-plugin/plugin.json

{
  "name": "data-scientist",
  "description": "AI/ML/LLM optimization — prompt engineering, token optimization, A/B testing, scientific studies",
  "version": "1.0.0",
  "author": {
    "name": "nagisanzenin"
  },
  "license": "MIT",
  "keywords": [
    "data-science",
    "ai",
    "ml",
    "llm",
    "prompt-engineering",
    "optimization",
    "ab-testing"
  ]
}