This repository contains an experimental educational prototype designed to identify potential signals associated with misinformation in news headlines or short textual content. The tool is implemented as a standalone HTML and JavaScript application that runs entirely in the browser without requiring external APIs, servers, or internet connectivity. Its purpose is to support media literacy and encourage critical evaluation of online information. The prototype analyzes user-provided text using a rule-based approach and highlights patterns commonly associated with misleading or unreliable content. These indicators include: - alarmist or sensational language - clickbait-style expressions - absence of explicit references to sources - absolute or exaggerated claims - emotionally charged wording - conspiracy-style narratives - sensational punctuation patterns Based on these indicators, the tool generates a simple risk score and a visual traffic-light style assessment to help users reflect on the credibility of the analyzed text. This prototype is intended strictly for educational and research purposes and should not be considered an automated fact-checking system. The project represents an early experimental version and may evolve in future versions. The objective is to support media literacy and facilitate research on misinformation detection patterns. Author. Jose Ranero García (2026). Educational Prototype for Detecting Potential Misinformation Signals in News Texts (HTML Tool) (v1.0). Zenodo. DOI: 10.5281/zenodo.18909909