readability-scorer Connector for AI agents.

Yes, it uses the Flesch-Kincaid algorithm to provide a mathematically accurate grade level score for any text you provide.

It doesn't rely on the LLM's memory or patterns. It routes your text through a Javascript engine that performs actual math on the characters.

Yes, you can specify a custom Words Per Minute (WPM) count to get a reading time that fits your specific audience.

Absolutely. It helps you ensure your content is accessible and readable, which are key factors for keeping users engaged on your site.

It is a readability test that estimates the years of education needed to understand a text. It specifically looks at sentence length and complex words.

Yes, you can provide long strings of text, and the Connector will process them to give you the total scores for the entire piece.

Readability formulas require knowing the exact number of phonetic syllables. LLMs process text in semantic tokens (e.g., 'unbelievable' might be 2 tokens, but it has 5 syllables). They cannot count syllables accurately, making algorithmic capabilities mandatory.

The syllable counting heuristic is highly optimized for English, which is the baseline for Flesch-Kincaid. However, the reading time and basic word/sentence extraction work flawlessly across all Latin-script languages.

No. We utilize a custom Regular Expression syllable engine built natively into the TypeScript architecture, achieving 0ms latency processing without downloading external NLP packages.