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.