Content Analyzer
Analyse word counts, Flesch readability scores, long sentences and repeated phrases, with highlighted suggestions.
AI and Content ProductivityAI and Content Productivity
AI and Content Productivity is about the unglamorous work that makes content good: checking that a draft is readable, consistent and honest before it ships. The Content Analyzer reports the measurable properties of your text — word and sentence counts, Flesch reading scores with the formulas shown, long sentences flagged for editing, repeated words and phrases, and passive-voice indicators — and it states its limits plainly: readability formulas estimate surface difficulty, they do not judge accuracy, originality or authorship. Alongside the analyzer, this category hosts our prompt-template library as static content: reusable, tested prompt structures for common writing jobs, each with notes on when it works and when it fails. The goal is a calmer workflow: draft with whatever tools you like, then verify with instruments you can see inside. Every suggestion the analyzer makes is highlighted in your text so you can accept, reject or rewrite it yourself — nothing is silently changed, and your text is never uploaded.
Tools in this category
Word Counter
Count words, characters, sentences and paragraphs, with reading and speaking times and one-to-three-word keyword density.
AI and Content ProductivityWhich tool should I use?
| Tool | Use it when you need to… |
|---|---|
| Content Analyzer | Analyse readability, sentence length and repetition in a draft, with formulas shown and limits stated honestly. |
Working notes
Use the analyzer at the end of the editing pass, not during drafting. Draft for meaning first; then run one pass for surface problems — the paragraph where every sentence runs past thirty words, the phrase repeated six times, the section that drifted into passive constructions. Fix what the highlights show, ignore what they get wrong, and remember the score is a proxy: a text can score well and still be inaccurate, which is why our guides pair every readability check with source checking. Templates from the library work the same way — structure first, judgement always.
Related articles
How to Improve Content Readability
Readability improves through editing, not score-chasing: shorten the longest sentences, cut complex words where a plain one works, and use Flesch, Flesch–Kincaid and Fog scores as diagnostics — with a before/after passage scored by the published formulas.
How to Write Better Prompts and Reusable Templates
Better prompts are built, not found: state the objective, give the context the model cannot guess, set constraints, show one example, and specify the output format — then turn what works into a reusable template with slots.
How to Check Facts in AI-Assisted Writing
A repeatable fact-check for AI-assisted drafts: extract every checkable claim, verify each against a primary source, record the verdict, and fix or flag what fails — demonstrated on a real paragraph with two planted-style errors caught.
Frequently asked questions
Can the Content Analyzer detect AI-written text?
No, and it says so on the tool page. Readability scores measure surface features like sentence length and syllable counts. They say nothing about who or what wrote the text, and tools that claim otherwise are guessing.
What does a readability score actually measure?
Flesch Reading Ease estimates how easy a text is to read from average sentence length and syllables per word. Higher is easier. It is a useful editing signal for spotting dense passages, not a quality grade for ideas or accuracy.
How do prompt templates help content work?
A template fixes the structure of a request — objective, context, constraints, examples, output format — so results are consistent across a team. Our prompt-writing guide walks through building one and testing it.