Recommend Tools

A curated catalog. Not every corpus problem should be solved inside Claude Code — sometimes the right move is to point at an established library and set the user up to use it.

Classical NLP toolkits

• spaCy — production-grade NLP: tokenization, POS, NER, dependency parsing, lemmatization. Use as the default for anything ner-extraction, parametric-analysis, or tokenization-heavy.
• TextBlob — friendly wrapper over NLTK/pattern. Good for quick sentiment, noun-phrase extraction, translation, simple classification on small corpora. Lower quality than spaCy/transformers but very approachable.
• NLTK — classic toolkit, strong for linguistic/academic work. Slower than spaCy for production.
• TextAnalysis.jl — the main NLP library for the Julia ecosystem. Reach for this when the user is already in Julia (scientific computing, notebooks) — covers document representations, TF-IDF, LDA, summarization, sentiment.

Topic modeling & clustering

• BERTopic — default recommendation for topic-analysis. Embeddings + UMAP + HDBSCAN + c-TF-IDF. Dynamic topics over time built-in.
• gensim — LDA, LSI, word2vec. Use when BERTopic is overkill or when LDA is explicitly wanted.
• Top2Vec — similar space to BERTopic.

Aspect-based sentiment / fine-grained opinion