polars SKILL.md skillA
polars from k-dense-ai/scientific-agent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add k-dense-ai/scientific-agent-skills/polars@v1.4Pins v1.4 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- k-dense-ai/scientific-agent-skills
- Path
skills/polars/SKILL.md- Versions recorded
- 6
- Latest version
- v1.4, committed Oct 1, 2026
- First version recorded
- May 27, 2026
- Size
- 13,139 bytes
- Repository stars
- 56,497
- License
- MIT
High-performance DataFrame library for Python ETL, analytics, and pandas migration. It supports expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Polars
## Overview
Polars is a columnar DataFrame library for Python and Rust with Arrow interoperability. Work with Polars' expression-based API, lazy evaluation framework, and high-performance data manipulation capabilities for efficient data processing, pandas migration, and data pipeline optimization.
Reviewed against the official stable documentation and native Polars 1.44.2. Local
regression tests cover the corrected APIs and scientific failure cases; cloud, GPU,
BigQuery, and remote database recipes are illustrative and require provider setup.
Fragments using undefined columns, paths, or `...` require adaptation to the dataset.
## Quick Start
### Installation and Basic Usage
Install the current stable Polars release verified during this refresh:
```bash
uv pip install "polars==1.44.2"
```
Install optional integrations only when needed:
```bash
uv pip install "polars[excel,database,fsspec,pandas,numpy]==1.44.2"
```
Basic DataFrame creation and operations:
```python
import polars as pl
# Create DataFrame
df = pl.DataFrame({
"name": ["Alice", "Bob", "Charlie"],
"age": [25, 30, 35],
"city": ["NY", "LA", "SF"]
})
# Select columns
df.select("name", "age")
…Read the whole file at its exact version.
How to install
mdr add k-dense-ai/scientific-agent-skills/polars@sha256:05d64a001190b516The line at the top of this page pins the label v1.4, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_j6o6ssu456r4ew5u)
6 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 6 versions of this file, between May 27, 2026 and Oct 1, 2026, about one every 25 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.4 latest | 2026-10-01 | a92663a | 13,139 B | A | view · diff |
| v1.3 | 2026-09-30 | ce9e6e9 | 10,821 B | A | view · diff |
| v1.2 | 2026-09-02 | 1e5eeff | 10,753 B | A | view · diff |
| v1.1 | 2026-07-26 | b085e11 | 9,796 B | A | view · diff |
| git:20260611.1b8fae3 | 2026-06-11 | 1b8fae3 | 9,801 B | A | view · diff |
| v1.0 | 2026-05-27 | 0936740 | 9,446 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (13139 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
k-dense-ai/scientific-agent-skills · 56,497 stars · license MIT · pushed 2026-11-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_j6o6ssu456r4ew5u GET https://markdownregistry.com/api/v1/resolve?ref=k-dense-ai/scientific-agent-skills/polars GET https://markdownregistry.com/api/v1/blob/05d64a001190b516bc922bac616483c3109a6d29c3e9950e3e2d6c31b9415e79
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
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