Holddrespell@R16 Voltagent Awesome Agent Skills Datascience

---
name: "r00-VoltAgent-awesome-agent-skills--datascience"
description: >
  🤖 Data Science & AI/ML skill suite derived from VoltAgent/awesome-agent-skills.
  Data pipelines, model training, evaluation, MLOps and analytical reporting.
  Provides 10 specialised commands for data-science, machine-learning, analytics workflows.
version: "1.0.0"
domain: datascience
tags: ["data-science", "machine-learning", "analytics", "pandas", "mlops"]
source: "https://github.com/VoltAgent/awesome-agent-skills"
license: MIT
---

# 🤖 Data Science & AI/ML Skill Suite

> Derived from **VoltAgent/awesome-agent-skills** · Focus: _1000+ agent skills from official dev teams and community_

## Overview

This skill provides 10 production-ready commands tailored for
**Data Science & AI/ML** workflows. All commands follow a consistent
interaction pattern with structured output, progress tracking and
actionable recommendations.

## Available Commands

- `/data-profiling` — Automated EDA report: distributions, nulls, outliers, correlations and drift
- `/feature-engineer` — Feature importance analysis with SHAP values and automated encoding recipes
- `/model-evaluate` — Model performance dashboard: ROC, PR curves, confusion matrix and bias check
- `/pipeline-scaffold` — Modular ML pipeline scaffold with versioning, logging and registry hooks
- `/ab-test-design` — Statistical A/B test design: sample size, power, MDE and sequential testing
- `/sql-optimize` — Query plan analysis, index recommendations and cost estimation
- `/dashboard-spec` — BI dashboard specification from KPI list with chart types and data sources
- `/data-contract` — Schema validation, SLA definition and data quality contract generation
- `/llm-eval` — LLM output evaluation harness: hallucination rate, faithfulness and latency
- `/anomaly-detect` — Time-series anomaly detection with root-cause attribution and alert tuning

## Interaction Pattern

Every command follows this structured response format:

```
1. CONTEXT CHECK   — Verify inputs and confirm scope with user
2. ANALYSIS        — Deep analysis with live progress display
3. FINDINGS TABLE  — Structured results with severity / priority
4. RECOMMENDATIONS — Prioritised action list (quick wins first)
5. NEXT STEPS      — Suggested follow-up commands
```

## UI Conventions

| Symbol | Meaning              |
|--------|----------------------|
| ✓      | Passed / complete    |
| ✗      | Failed / critical    |
| ⚠      | Warning / review     |
| ⟳      | In progress          |
| ░      | Pending              |
| 🔴     | Critical severity    |
| 🟠     | High severity        |
| 🟡     | Medium severity      |
| 🟢     | Low / informational  |

Progress bars use block characters:
`[████████░░] 80%`

## Quick Start

```bash
# Install this skill
cp -r . ~/.claude/skills/r00-VoltAgent-awesome-agent-skills--datascience/

# In Claude Code
/read ~/.claude/skills/r00-VoltAgent-awesome-agent-skills--datascience/SKILL.md
```

Then simply describe your task and Claude will route to the
appropriate command automatically.