DSC Extractor

Purpose & User Intent: The DSC Extractor solves the problem of extracting structured descriptions, metadata, and keyword ideas from unstructured content. Target users include content editors, SEO analysts, marketers, researchers, and product teams. When to use: during content audits, metadata enrichment, and before publishing to ensure consistent descriptors.
Core Logic & Features: Domain-aware parsing identifies descriptive phrases, key nouns, and topical signals to generate a clean description, a set of SEO-ready metadata fields, and a prioritized keyword list. Required features include input parsing of text/HTML/URLs, extraction of description sentences, title/slug suggestions, meta description generation, and keyword clustering. Optional/advanced features include language-aware normalization, duplicate detection, and export in JSON/CSV.
Inputs & Outputs: Accepts input text, HTML, Markdown, or URL; outputs include description text, meta description, title suggestions, and a keywords array; validation enforces length and character constraints.
Algorithms & Calculations: Uses heuristic sentence extraction, part-of-speech tagging to identify descriptors, TF-IDF or simple frequency-based keyword ranking, and length checks for title/description; applies SEO best-practices for meta fields.
Error & Edge Cases: Handles missing inputs by returning empty outputs; detects non-HTML or malformed URLs; notes external data unavailability and rate limits; normalizes content in various encodings.
Industry/Region & Localization: Aligns with common SEO standards; defaults to English (en) with potential localization hooks; length constraints for meta and description sections reflect typical search engine limits.
Assumptions & Exclusions: Assumes input content is accessible and permitted; excludes UI rendering, content generation beyond metadata, and behind-authentication content; not a plagiarism detector.