Skills

A skill is a package of structured files that teaches an AI coding agent how to work with a specific tool or framework. The skill below was generated by Great Docs from this project’s documentation. Install it in your agent and it will be able to run commands, edit configuration, write content, and troubleshoot problems without step-by-step guidance from you.

Any agent — install with npx:

npx skills add https://github.com/rich-iannone/example-python-package#readme/

Codex / OpenCode

Tell the agent:
Fetch the skill file at https://github.com/rich-iannone/example-python-package#readme/skill.md and follow the instructions.

Manual — download the skill file:

curl -O https://github.com/rich-iannone/example-python-package#readme/skill.md

Or browse the SKILL.md file.

SKILL.md

---
name: tinytab
description: >
  An example Python package for learning how to package and test a library. Use when writing Python code that uses the tinytab package.
license: MIT
compatibility: Requires Python >=3.10.
---

# tinytab

An example Python package for learning how to package and test a library.

## Installation

```bash
pip install tinytab
```

## API overview

### Formatting values

Turn single values into display strings.

- `fmt_number`: Format a number with a fixed number of decimal places and a thousands separator
- `fmt_percent`: Format a proportion as a percentage
- `fmt_currency`: Format a number as a currency value

### Tables

Build a table, format its columns, and render it as text or HTML.

- `Table`: A small, column-oriented table
- `Table.fmt`
- `Table.as_text`
- `Table.as_html`
- `Table.to_csv`
- `Table.from_csv`

### Summary statistics

Summarize a set of numbers.

- `summarize`: Compute summary statistics for a sequence of numbers
- `SummaryResult`: Summary statistics for a set of numbers, as returned by `summarize()`

## Resources

- [Full documentation](https://github.com/rich-iannone/example-python-package/)
- [llms.txt](llms.txt) — Indexed API reference for LLMs
- [llms-full.txt](llms-full.txt) — Comprehensive documentation for LLMs
- [Source code](https://github.com/rich-iannone/example-python-package)