The sample text
I am excited to apply for the Marketing Coordinator position at your company. I am excited to bring my skills in content creation and social media management to your team. With three years of experience in digital marketing, I have developed a strong ability to craft compelling campaigns. I have developed a strong ability to analyze performance data and adjust strategy accordingly. I believe my background makes me a great fit for this role, and I look forward to the opportunity to contribute to your team’s continued success.
What the local engine measured
| Statistic | Value |
|---|---|
| Words | 88 |
| Sentences | 5 |
| Average words per sentence | 17.6 |
| Sentence-length variation (CV) | 0.26 |
| Vocabulary ratio (unique / total words) | 0.67 |
| Repeated sentences | 0 |
| Estimated reading time | 0.39 min |
What this does and does not show
Hiring teams increasingly ask whether a short cover letter reads as formulaic because a candidate used a chatbot to draft it, or simply because cover letters share a narrow, polite register. TextClueCheck cannot answer "who wrote this." What it can show is whether a passage repeats itself, how varied the sentence lengths are, and how many distinct words appear relative to the total word count, all of which are observable regardless of authorship.
The sample above intentionally echoes a common cover-letter pattern: two sentences that open the same way ("I am excited to...", "I have developed a strong ability to..."). That kind of templated repetition shows up in both AI-drafted and heavily reused human boilerplate, including cover letters recycled across applications. A hiring manager who notices this pattern has a fair reason to ask a candidate to speak to the role in their own words during an interview, not to reject the application on the statistic alone.
Open this passage in the live tool
Source: TextClueCheck local evidence engine, run on this page's own sample text at build time (2026-09-25). Not an AI-authorship probability.