Single tool with acceptable naming (get_documentation) but significant gaps in schema completeness, parameter descriptions, and output documentation. The tool description is adequate (108 chars, within 10-1024 range) but parameter descriptions are minimal. No output schema documented. Error handling is basic (ValueError for unsupported library, generic timeout/no-results strings). The implementation exposes external API dependency (SERPER_API_KEY) via environment variable (good), but lacks structured output and pagination guidance.

• Define output schema explicitly: return {results: [{source_url: string, title: string, excerpt: string, relevance_score: number}], total_results: number, query_used: string}. This enables LLM chaining and structured parsing.
• Convert library parameter to enum: {type: 'string', enum: ['pytorch'], description: 'The library to search in. Currently only PyTorch is supported.'}
• Add query parameter constraints: 'The search query (1-200 characters). Examples: "torch.randn", "how to use autograd". Avoid URLs and code snippets.'
• Implement result limiting and pagination: accept optional limit (default 5, max 20) and offset parameters. Return total_results count to enable agent-driven pagination.
• Enhance error messages with recovery guidance: 'No results found for "X". Try: (1) simplify the query, (2) search for a related function, (3) use search_pytorch_tutorials() instead.'