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DataPython

Data Analysis Loop

by gaasher

Data Analysis Loop is a Data skill for Claude Code, published by gaasher in Agent-Loop-Skills.

166 stars19 forkson gaasher/Agent-Loop-SkillsAdded 2026/09/08+2% in starsRepository updated 2026/06/30
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agent-skillsagentic-loopsagentic-workflowsai-agentsanthropicautoresearchclaudeclaude-codedata-analysisliterature-reviewllm-agentsmachine-learningml-autoresearchopen-sourceprompt-engineeringred-teamingscientific-writingskillssubagents
Install in seconds
Install Data Analysis Loop
Copy Data Analysis Loop into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.
terminal
npx degit https://github.com/gaasher/Agent-Loop-Skills/tree/main/loops/data-analysis ~/.claude/skills/data-analysis

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/gaasher/Agent-Loop-Skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file
loops/data-analysis/SKILL.md in gaasher/Agent-Loop-Skills
Installs to
~/.claude/skills/data-analysis
Collection
One of 25 skills cataloged from this repository
Category
Data — 812 skills

What Data Analysis Loop does

Data Analysis Loop performs iterative exploratory analysis on a dataset, testing one hypothesis at a time and only keeping findings that reproduce with a meaningful effect size. Use it for open-ended discovery when every claim needs a computed number behind it.

Data Analysis Loop is cataloged under Data on DirSkills. Data Analysis Loop comes from a repository tagged agent-skills, agentic-loops, agentic-workflows, ai-agents and anthropic.

Documentation

README

Data Analysis Loop

A hypothesis → verify reflection loop over a dataset. The artifact is a findings report; the feedback signal is verification — a finding only counts if re-running the computation confirms it at a meaningful effect size. The discipline this enforces: no insight without a number behind it. A plausible claim the data does not support is discarded, not softened; every line in the report can be reproduced from the dataset.

When to use

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Data Analysis Loop

  • What else does gaasher publish alongside Data Analysis Loop?

    Data Analysis Loop is one of 25 skills that DirSkills catalogs from gaasher/Agent-Loop-Skills, the repository it ships in. Its siblings there include Alpha Evolve, Anomaly Investigation and Blue Team. Each one is a separate skill with its own page in this directory, installs the same way Data Analysis Loop does, and is maintained by gaasher in that same repository. The rest of the collection is listed on the gaasher/Agent-Loop-Skills page.

  • How does Data Analysis Loop compare to other Data skills?

    Data Analysis Loop ranks #754 by stars among the 812 Data skills in this catalog. The most-starred ones next to it are Benchmark Methodology, Jupyter Notebook and Solana. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Data Analysis Loop against them. Open each page to compare what they document and how they install.

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