executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
similarity-searchScore text pairs and run dense or BM25 retrieval with text2vec.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this sub-skill when you need sentence similarity, pair scoring, semantic search, or lexical BM25 retrieval in text2vec.
Similarity, SimilarityType, EmbeddingType, get_score, get_scores, and similarity.cos_sim and semantic_search for tensor or NumPy embeddings.embeddings.training-finetuning.evaluation-benchmarks.serving-deployment.scripts/score_pairs.py: score aligned text pairs from JSONL, CSV, or TSV using supplied vectors or Similarity.scripts/search_corpus.py: search a corpus with BM25 or dense embeddings and return top-k hits.Start with references/workflows.md for ready-to-run patterns and references/api-reference.md for return shapes.