Single tool 'ask_documents' has a basic description and input schema, but critical gaps in parameter documentation, output schema specification, and error handling guidance. The description is adequate (84 chars, within baseline range of 34-392) but lacks context on when to use it, prerequisites, and expected outputs. The single parameter 'question' lacks format guidance, length constraints, or examples of good/bad inputs. No documented output schema, LLMs cannot plan downstream actions or extract specific fields. Error handling is absent, no guidance for recovery if PDF ingestion fails, vector search finds no results, or the LLM provider errors. Schema is present but minimal. Naming is reasonable but could be more specific (ask_documents_question vs search_documents would be clearer). No tool annotations (readOnlyHint/idempotentHint). Per pattern:tool, pattern:tool-description, and review:incomplete-docstrings, this server falls short of production expectations.

• Add a full description to the 'question' parameter: 'The question to ask about the ingested PDF documents. Should be 1-500 characters; longer questions may be truncated by the embedding model. Examples: "What are the key findings?" or "Summarize the methodology." Avoid questions requiring information not in the PDFs, the tool only searches ingested documents.'
• Document the output schema explicitly in code comments or a README. The response format is {content: [{type: 'text', text: '<answer text>'}]}. Explain that answer may be empty or incomplete if no relevant context was found.
• Expand the tool description to include: '(1) WHAT: Answers questions by searching ingested PDFs and generating responses grounded in retrieved context. (2) WHEN: Use when you need factual information from uploaded documents. (3) PREREQUISITES: PDFs must be ingested first via the ingest process. (4) LIMITATIONS: Only searches documents in the vector store; external knowledge is not available.'
• Add error handling and recovery guidance in the response. When no vector results are found (empty context), return a clear message: 'No relevant content found in the ingested documents. Try rephrasing your question or check that the required PDF has been ingested.' This guides the agent to retry or suggest document upload.
• Add tool annotations to the server registration: registerTool('ask_documents', {description: '...', readOnlyHint: true, idempotentHint: true, inputSchema: {...}}). This signals to the agent that the tool is safe to call repeatedly without side effects.