r00-behisecc-awesome-claude-skills-datascience

🤖 Data Science & AI/ML skill suite derived from BehiSecc/awesome-claude-skills. Data pipelines, model training, evaluation, MLOps and analytical reporting. Provides 10 specialised commands for data-science, machine-learning, analytics workflows.

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Aperçu

Commande d'installation

npx skills add https://github.com/Winnershitram/r17-behisecc-awesome-claude-skills-datascience --skill r00-behisecc-awesome-claude-skills-datascience

Copiez et collez cette commande dans Claude Code pour installer le skill

Source

Winnershitram/r17-behisecc-awesome-claude-skills-datascience

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Mis à jour28 avril 2026 à 18:34

SKILL.md

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Source

Winnershitram

Winnershitram/r17-behisecc-awesome-claude-skills-datascience

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Commande d'installation

Téléchargement

Exécuter dans Manus

Utile pourSOC

Scientifiques des donnéesProfessions informatiques et mathématiques15-2051L4

name	r00-BehiSecc-awesome-claude-skills--datascience
description	🤖 Data Science & AI/ML skill suite derived from BehiSecc/awesome-claude-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/BehiSecc/awesome-claude-skills
license	MIT

🤖 Data Science & AI/ML Skill Suite

Derived from BehiSecc/awesome-claude-skills · Focus: curated list of Claude Skills

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

# Install this skill
cp -r . ~/.claude/skills/r00-BehiSecc-awesome-claude-skills--datascience/

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

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