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Found 7 Skills
Split text into contextual chunks for RAG/embedding pipelines. Document segmentation and section extraction using window, tfidf, punctuation, or hybrid strategies chosen by intent.
Implement TF-IDF scoring to measure term importance relative to a document corpus. Use this skill when the user needs to rank documents by keyword relevance, extract important terms from text, or build a basic search relevance engine — even if they say 'find relevant documents', 'keyword extraction', or 'term importance'.
Build and maintain a topic graph over your agent session history. Reads every Claude session transcript plus the pruned sessions that survive only in history.jsonl, clusters them by topic using local TF-IDF (no API calls, no embeddings), and writes an interactive graph you can open in a browser. Use when the user says "/session-brain", "build my session map", "cluster my claude sessions", "map my session history", "rebuild the session graph", "show me my session graph", "what have I been working on lately", "what topics have gone stale". Different from wiki-history-ingest, which distils sessions into vault pages: this builds a retrieval index over the raw sessions and never writes to the vault.
Extract keywords and key phrases from text using TF-IDF, RAKE, and frequency analysis. Generate word clouds and export to various formats.
Implement BM25 ranking function for e-commerce product search relevance scoring. Use this skill when the user needs to build a text-based product search engine, improve search result relevance, or replace basic TF-IDF with a more robust ranking function — even if they say 'product search ranking', 'search relevance', or 'BM25 implementation'.
Compare document similarity using TF-IDF, cosine similarity, and Jaccard index. Use for plagiarism detection, duplicate finding, or content matching.
Knowledge Base Injection is the technique of dynamically injecting domain expertise into an agent's context at the moment it is most relevant, using TF-IDF pattern matching and semantic scoring.