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polars

85 / 100 · Low risk

Fine to try.

By roohe/agentic-super-skills (GitHub) · data · 10 stars · scanned at commit f483e54

Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.

Works with any agent that supports SKILL.md skills.

What this skill can do

Downloads and installs other software

The author does not mention this.

Found in 1 place.

Install

Paste this into your terminal. It downloads exactly the version we scanned, not whatever is newest.

if [ -e ~/.agents/skills/'polars' ] || [ -L ~/.agents/skills/'polars' ]; then echo 'A skill folder named polars already exists — not replacing it' >&2; false; else d=$(mktemp -d) && git clone --quiet --filter=blob:none --no-checkout 'https://github.com/roohe/agentic-super-skills' "$d" && git -C "$d" checkout --quiet 'f483e54f3ad5f202a77d45f2e57f8d970b71195f' -- 'skills_library/polars' && mkdir -p ~/.agents/skills && cp -R "$d"/'skills_library/polars' ~/.agents/skills/'polars' && rm -rf "$d"; fi

Codex reads ~/.agents/skills directly. For Claude Code, Cursor, Copilot, Gemini CLI, Antigravity or OpenCode, also link it. For Claude Code: ln -s ~/.agents/skills/'polars' ~/.claude/skills/'polars' (other agents: ~/.cursor/skills, ~/.copilot/skills, ~/.gemini/skills, ~/.gemini/config/skills, ~/.config/opencode/skills). Or install through the finder skill, which does both.

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Score history

DateVersionScore
2026-11-08f483e5485

Also found in

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