Rag Architect

alirezarezvani/claude-skills/engineering/skills/rag-architect

作者 alirezarezvani19392f7a0826無授權條款27K 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫5 週前更新

Use when the user asks to design a RAG pipeline, choose a chunking strategy or embedding model, pick a vector database, or evaluate retrieval quality (precision@k, recall@k, NDCG). Examples: 'design a RAG system for our docs', 'what chunk size should I use for this corpus', 'evaluate my retriever against ground truth'. NOT for general LLM cost tuning (use llm-cost-optimizer) or agent loops over retrieval (use agenthub).

包含腳本AI & Agents

僅公開檔案列表。將技能安裝到工作區後即可檢視檔案內容。

路徑大小類型
chunking_optimizer.py28.8 KBtext/plain
rag_pipeline_designer.py27.6 KBtext/plain
references/chunking_strategies_comparison.md9.9 KBtext/markdown
references/embedding_model_benchmark.md12.4 KBtext/markdown
references/rag_evaluation_framework.md14.8 KBtext/markdown
retrieval_evaluator.py23 KBtext/plain
SKILL.md4.4 KBtext/markdown

來源與署名

來源:alirezarezvani/claude-skills位於engineering/skills/rag-architect提交19392f7

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