rag-search

# RAG Search Skill ## Instructions When the user asks about internal policies, documentation, procedures, or knowledge base content, use the `rag_search` tool to retrieve relevant content from the Azure AI Search knowledge base. **IMPORTANT**: Always pass `index_name: "knowledge-base"` when calling `rag_search`. This is the dedicated search index for the generic knowledge base. ### 1. When to Use Use this skill when the user's question relates to: - Internal documentation, policies, or procedures - Product or service information stored in the knowledge base - Reference material, FAQs, or how-to guides - Any question that should be grounded in authoritative internal content **Do NOT use** for: real-time web data (→ `web_search`), calculations (→ `code_interpreter`). ### 2. Craft the Search Query - Be specific with domain terms rather than generic phrases - Include the key concept and context (e.g., "onboarding process new employee" rather than just "onboarding") - If the first query returns low-relevance results, rephrase with synonyms or more specific terms ### 3. Interpret Search Results Results contain: title, content, source, page, relevance score. - **Synthesize** multiple results into a coherent answer rather than dumping raw excerpts - **Cite sources** with document title and page number (e.g., "Per the *Employee Handbook*, p. 12...") - **Quote exact wording** when precision matters (policies, procedures, requirements) - **Flag gaps** — if the retrieved content doesn't fully answer the question, say so explicitly - **Note confidence** — if results have low relevance scores, mention that the information may not be complete ### 4. Multi-Step Workflows Combine RAG search with other skills for richer answers: - **Knowledge + summary**: `rag_search` → `document_summary` to condense retrieved content - **Knowledge + analysis**: `rag_search` → `code_interpreter` to analyze data referenced in docs - **Knowledge + web verification**: `rag_search` → `web_search` to check if internal info is still current - **Knowledge + email**: `rag_search` → `email_draft` to compose a response grounded in policy ### 5. Response Guidelines - Present information clearly and accurately — do not paraphrase in ways that change the meaning - Use bullet points or tables for structured information - Always include the source document and page reference - If multiple documents are relevant, present findings from each and note any differences - If no relevant results are found, say so clearly and suggest the user refine their query ### 6. Error Handling If the search returns an error or no results: - Report the issue transparently to the user - Suggest alternative search terms - Offer to try `web_search` as a fallback if appropriate