name: data-pro-max description: "Data Analysis Intelligence Orchestrator. Master skill that coordinates specialized competencies for end-to-end data pipelines: (1) Data Analysis Suite (Stats/Causal/Science), (2) Geoprocessing Brazil, (3) Data Viz, and (4) Document Converter (Import/Export/Mermaid)."

Data Pro Max - Data Analysis Intelligence

An AI orchestrator that provides intelligent recommendations for data analysis, visualization, and reporting. It automatically activates for data-intensive tasks and coordinates specialized sub-skills.

1. Integrated Skill Cores

Data Pro Max coordinates these specialized skills:

Core Skill	Functionality	Location
`data-manipulation`	T-Layer (Preparation, Weights, Map)	📦 `data/skills/`
`data-analysis-suite`	All Stats, Causal & Science	📦 `data/skills/`
`geoprocessing-brazil`	Geo-spatial & Mapping	📦 `data/skills/`
`data-viz`	Statistical Visualization	📦 `data/skills/`
`document-converter`	Format Conversion (Import/Export)	📦 `data/skills/`
`duckdb-sql-master`	High-performance SQL on local files	📦 `data/skills/`
`time-series-analysis`	Validation & metrics for sequence data	📦 `data/skills/`
`clustering-toolkit`	Advanced PCA+DBSCAN grouping	📦 `data/skills/`
`context-optimizer`	Document decomposition into .agent	📦 `data/skills/`

Shared Skills (deployed via manifest)

Skill	Purpose	Location
`brainstorming`	Creative ideation & design	🔗 `.agent/skills/` → manifest
`document-mastery`	Writing quality & Mermaid diagrams	🔗 `.agent/skills/` → manifest

Agent-Only Skills (NOT deployed)

Skill	Purpose	Location
`skill-creator`	Creating and packaging new skills	🏠 `.agent/skills/`
`notebooklm`	Querying Google NotebookLM notebooks	🏠 `.agent/skills/`

2. Master Workflows (Slash Commands)

Command	Workflow	Location
`/project-onboarding`	Initial setup & rules	📦 Packaged (`datapro setup`)
`/survey-analysis-pipeline`	End-to-end execution	📦 Packaged (`datapro setup`)
`/project-harvest`	Learning extraction → `assets/harvest/`	📦 Packaged (`datapro setup`)
`/document-study`	Deep analysis of papers/methodology	📦 Packaged (`datapro setup`)
`/notebook-generation`	Dual-layered automated notebook reporting	📦 Packaged (`datapro setup`)
`/project-evolution`	Absorb harvest into Data-Pro-Skill	🏠 Local (this repo only)

3. High-Performance Workflow

graph TD
    A[User Request] --> B[Data Discovery]
    B --> C{Orchestrator}
    C -->|Transformation| D1[data-manipulation]
    C -->|Statistical| D2[data-analysis-suite]
    D1 --> D2
    C -->|Spatial| E[geoprocessing-brazil]
    C -->|SQL/Large Data| F[duckdb-sql-master]
    D1 & D2 & E & F --> G[data-viz]
    G --> H[document-mastery]
    H --> I[document-converter]
    I --> J[Final Report]

4. Operational Best Practices

Step 1: Integrated Pipeline

Use @data-manipulation for preparation (mapping, cleaning, weighting) and @data-analysis-suite for specialized statistics. Consult the references/*.md inside each skill for specific methodologies.

Step 2: Consistent Aesthetics

Always use data-viz for chart generation to ensure consistent styling and 300 DPI quality.

Step 3: Global Language Policy

All technical artifacts, code comments, and documentation produced MUST be written in English.

[!IMPORTANT] This repository uses a References Pattern for complex skills. If a task requires specialized stats, read the corresponding file in data-analysis-suite/references/ first.

Name	survey-data-viz
Description	Generates professional statistical charts (Bar, Pie, Grouped) using Matplotlib and Seaborn. Use this skill to visualize survey data, trends, and distributions for reports. Optimized for survey-specific needs like 'Before vs After' evolution charts and premium aesthetics.

survey-data-viz

SKILL.md