wtf is papa?

Papa is a readability checker for Markdown and plain text documents. It works like the Hemingway Editor, the popular web app that highlights hard-to-read sentences, but Papa is designed to run from the command line and fit into automated workflows. You can use it as a standalone command-line tool, as a Python library, or inside continuous integration pipelines to enforce writing quality standards on your documentation. It is currently alpha software, meaning it is still in early development. The tool scans your writing and assigns a readability grade using three established formulas: ARI, Flesch-Kincaid, and Gunning fog. It also flags specific problems in your prose, including sentences that are hard to read, passive voice, adverbs, and complex phrasing. When it processes Markdown files, it safely skips over things like code blocks, frontmatter, and inline code so it only evaluates your actual prose. Papa can produce output in three formats. The default is a terminal view that shows the grade, a summary of flagged issues, and specific line numbers with explanations. You can also request a JSON file, which includes precise character offsets for each finding and is intended for use by scripts or automated agents. The third option is a self-contained HTML report that highlights the flagged sentences visually, similar to the Hemingway app, and works offline with no external dependencies. A key feature is the ability to gate continuous integration. You can set a maximum acceptable grade level, and if your documentation exceeds that threshold, the tool exits with an error code. This causes the CI job to fail, which means a pull request with overly complex prose cannot be merged until the writing is simplified. The same command can be run locally before submitting a pull request. The roadmap includes planned features such as a configuration file, a dedicated GitHub Action, additional output formats like SARIF and Markdown for pull request annotations, and integrations with other writing tools. The project is built on an existing Python library called textstat for its readability calculations and adds its own rules for the style findings.