From text-corpus-analysis
Count word/token occurrences across a corpus with stopword filtering, stemming/lemmatization options, and n-gram support. Use when the user wants a simple frequency export — "how often does X come up", "top 100 words in my notes", "bigram frequencies".
npx claudepluginhub danielrosehill/claude-code-plugins --plugin text-corpus-analysisThis skill uses the workspace's default tool permissions.
Classical, mechanical. No LLM involvement.
Provides UI/UX resources: 50+ styles, color palettes, font pairings, guidelines, charts for web/mobile across React, Next.js, Vue, Svelte, Tailwind, React Native, Flutter. Aids planning, building, reviewing interfaces.
Fetches up-to-date documentation from Context7 for libraries and frameworks like React, Next.js, Prisma. Use for setup questions, API references, and code examples.
Analyzes multiple pages for keyword overlap, SEO cannibalization risks, and content duplication. Suggests differentiation, consolidation, and resolution strategies when reviewing similar content.
Share bugs, ideas, or general feedback.
Classical, mechanical. No LLM involvement.
nltk.word_tokenize. For code-adjacent corpora, preserve underscores/hyphens.collections.Counter. For n-grams, nltk.ngrams or sliding window.word-frequency.csv: term, count, docs_containing, avg_per_doctrend-analysis.Trivial. Processes millions of docs on a laptop in minutes. No cost.
synonym-cluster first or you'll double-count variants ("GitHub", "git hub", "get hub").topic-analysis — word frequency alone misses paraphrases.