wrangling-skills

10 data wrangling skills. Trigger: messy data, format conversion, missing values, data reshaping. Design: pipeline-oriented recipes for common data cleaning and transformation tasks.

191 stars

Best use case

wrangling-skills is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

10 data wrangling skills. Trigger: messy data, format conversion, missing values, data reshaping. Design: pipeline-oriented recipes for common data cleaning and transformation tasks.

Teams using wrangling-skills should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/wrangling/SKILL.md --create-dirs "https://raw.githubusercontent.com/wentorai/research-plugins/main/skills/analysis/wrangling/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/wrangling/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How wrangling-skills Compares

Feature / Agentwrangling-skillsStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

10 data wrangling skills. Trigger: messy data, format conversion, missing values, data reshaping. Design: pipeline-oriented recipes for common data cleaning and transformation tasks.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Data Wrangling — 10 Skills

Select the skill matching the user's need, then `read` its SKILL.md.

| Skill | Description |
|-------|-------------|
| [csv-data-analyzer](./csv-data-analyzer/SKILL.md) | Load, explore, clean, and analyze CSV data with statistical summaries |
| [data-cleaning-pipeline](./data-cleaning-pipeline/SKILL.md) | Systematic data cleaning workflows for research datasets |
| [data-cog-guide](./data-cog-guide/SKILL.md) | Upload messy CSVs with minimal prompting for deep automated analysis |
| [missing-data-handling](./missing-data-handling/SKILL.md) | Diagnose missing data patterns and apply appropriate imputation strategies |
| [pandas-data-wrangling](./pandas-data-wrangling/SKILL.md) | Data cleaning, transformation, and exploratory analysis with pandas |
| [questionnaire-design-guide](./questionnaire-design-guide/SKILL.md) | Questionnaire and survey design with Likert scales and coding |
| [stata-data-cleaning](./stata-data-cleaning/SKILL.md) | Clean, transform, and validate messy research data using Stata |
| [streamline-analyst-guide](./streamline-analyst-guide/SKILL.md) | End-to-end data analysis AI agent with Streamlit UI |
| [survey-data-processing](./survey-data-processing/SKILL.md) | Clean, recode, and prepare survey response data for analysis |
| [text-mining-guide](./text-mining-guide/SKILL.md) | Apply NLP and text mining techniques to research text data |

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