Adjective Checker

This tool analyzes input text to identify adjectives and descriptive modifiers, returning counts, lemmas, and sample contexts to assist writers and editors in shaping tone. It supports content teams aiming to audit descriptive language, reduce overuse, and align with brand voice. By isolating adjectives, users can quantify descriptive density and compare usage across documents.

Conceptually, the system performs POS tagging to detect adjectives, then lemmatizes forms to canonical lemmas for stable counting. It outputs a structured list with word, lemma, count, POS tag, and sample_context showing how each adjective appears in context. Optional modules can score alignment with a target tone and propose synonyms to diversify language. The approach favors deterministic results given a model version, enabling reproducible audits in style guides and content reviews.

Who benefits: editors refining product descriptions, marketers testing sensory language, teachers evaluating student writing, and ESL learners studying adjective usage. Unique value lies in combined adjective-level analytics, context sampling, and optional tone suggestions, all without mutating the source text. Core features include: adjective extraction, per-token context capture, lemma-based counting, sample contexts, and export-ready formats for downstream workflows.