10x-Analyst

Agentic Analysis Automation Swarm
A proprietary multi-agent Claude Code plugin for end-to-end data analysis automation

Website · Quick Start · Commands · Architecture

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Proprietary Software — This plugin is the intellectual property of 10x.in and is developed, maintained, and owned by the 10x Team. All rights reserved. Unauthorized reproduction, distribution, or commercial use without explicit written permission from 10x.in is strictly prohibited. See LICENSE for details.

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What is 10x-Analyst?

10x-Analyst is a production-grade Claude Code plugin built by the 10x Team that transforms raw data into actionable insights, comprehensive reports, and interactive dashboards — fully automated through a coordinated swarm of five specialist AI agents.

Drop your data in, run one command, and get:

• Cleaned & profiled datasets
• Statistical analysis with EDA, correlations, and KPIs
• Publication-ready charts and visualizations
• Structured Markdown reports
• Interactive HTML dashboards
• Business recommendations and strategic action items

Quick Start

# 1. Place your data files in the input directory
#    input/my-dataset/data.csv

# 2. Run the full analysis pipeline
/10x-analyst:analyze my-dataset

# 3. Find all results in output/my-dataset/

A demo Shopify e-commerce dataset is included out of the box:

/10x-analyst:analyze shopify-data

Commands

Command	Description
/10x-analyst:analyze	Full agentic pipeline — ingest, clean, analyze, visualize, report, dashboard
/10x-analyst:profile	Data profiling and quality assessment
/10x-analyst:clean	Data cleaning and transformation
/10x-analyst:query	Ask natural language questions about your data
/10x-analyst:visualize	Generate charts and visualizations
/10x-analyst:report	Generate a comprehensive Markdown analysis report
/10x-analyst:dashboard	Build a standalone interactive HTML dashboard

Every command takes a dataset name as argument and reads from input/<dataset>/, writing results to output/<dataset>/.

Architecture

10x-Analyst coordinates 5 specialist agents through an orchestrator pipeline:

                        User Request
                             │
                             ▼
                   ┌───────────────────┐
                   │   ORCHESTRATOR    │
                   │  (Command Router) │
                   └────────┬──────────┘
                            │
         ┌──────┬───────────┼───────────┬──────────┐
         ▼      ▼           ▼           ▼          ▼
    ┌─────────┐┌──────────┐┌──────────┐┌────────┐┌──────────┐
    │  Data   ││  Stats   ││Visualizer││Reporter││Strategist│
    │ Engineer││  ician   ││          ││        ││          │
    └────┬────┘└────┬─────┘└────┬─────┘└───┬────┘└────┬─────┘
         │          │           │           │          │
         ▼          ▼           ▼           ▼          ▼
      Clean &    EDA &      Charts &    Markdown   Business
      Profile    Stats      Dashboard    Report    Actions

Agent Responsibilities

Agent	Role
Data Engineer	Ingest, profile, clean, and transform raw data files
Statistician	Exploratory data analysis, correlations, distributions, statistical tests, RFM segmentation
Visualizer	Matplotlib/Seaborn charts, Chart.js interactive HTML dashboards
Reporter	Assemble all findings into structured, publication-ready Markdown reports
Strategist	Interpret findings and generate business recommendations & prioritized action items

Pipeline Flow

Command	Agent Pipeline
:analyze	Data Engineer → Statistician → Visualizer → Reporter → Strategist
:profile	Data Engineer
:clean	Data Engineer
:query	Data Engineer → Statistician → Strategist
:visualize	Data Engineer → Visualizer
:report	Data Engineer → Statistician → Reporter → Strategist
:dashboard	Data Engineer → Statistician → Visualizer

Model Strategy

Model	Best For	Why
Opus	:analyze, complex :query	Maximum reasoning for deep analysis
Sonnet	:report, :dashboard, :query	Balanced quality and speed
Haiku	:profile, :clean, :visualize	Fast, token-efficient for scripted tasks

Supported Data Formats

Format	Extensions	Engine
CSV	.csv	pandas read_csv
Excel	.xlsx, .xls	pandas read_excel (openpyxl / xlrd)
JSON	.json	pandas read_json / json_normalize

Project Structure

10x-analyst/
├── .claude-plugin/plugin.json     # Plugin metadata
├── CLAUDE.md                      # Orchestrator — routes commands to agents
├── README.md                      # This file
├── input/                         # Data input directory
│   └── shopify-data/              # Demo dataset (included)
│       ├── customers.csv
│       ├── orders.csv
│       ├── order_items.csv
│       ├── products.csv
│       └── price_changes.csv
├── output/                        # Analysis output directory (auto-created)
├── agents/                        # 5 specialist subagent definitions
│   ├── data-engineer.md
│   ├── statistician.md
│   ├── visualizer.md
│   ├── reporter.md
│   └── strategist.md
├── skills/                        # 7 slash commands
│   ├── analyze/SKILL.md
│   ├── profile/SKILL.md
│   ├── clean/SKILL.md
│   ├── query/SKILL.md
│   ├── visualize/SKILL.md
│   ├── report/SKILL.md
│   └── dashboard/SKILL.md
├── references/                    # Shared knowledge base
│   ├── analysis-patterns.md
│   ├── chart-styles.md
│   └── data-quality.md
└── scripts/                       # Reusable Python utilities
    ├── profiler.py
    ├── data_cleaner.py
    ├── chart_generator.py
    └── dashboard_template.py

Requirements

• Python 3.8+
• pandas, matplotlib, seaborn (auto-installed if missing)
• openpyxl (for .xlsx), xlrd (for .xls)
• Chart.js CDN (for dashboard interactivity)

License

Proprietary Software — Copyright (c) 2024-2026 10x.in. All rights reserved.

This software and its associated documentation are the exclusive property of 10x.in. No part of this software may be reproduced, distributed, modified, or transmitted in any form or by any means without the prior written permission of 10x.in.

For licensing inquiries, contact the 10x Team at 10x.in.

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_{Built with precision by the 10x Team at 10x.in
10x-Analyst v1.0.0}