Single tool with minimal definition quality. Tool name 'web_search' is generic and lacks action clarity (should be 'search_web' or 'perform_web_search'). Description is 67 chars, below the 194-char baseline for production tools. Input schema present but parameter 'query' lacks description entirely, violates critical rule that every parameter needs a description. No output schema documented. Error handling returns plain text without recovery guidance. Tool does not follow verb_noun naming convention strongly enough.

• Add description to 'query' parameter: 'The search query string (1-500 chars). Can include keywords, phrases, or natural language questions.'
• Expand tool description to 150-250 chars explaining WHAT it does, WHEN to use it, and what it returns. Example: 'Performs web search using OpenAI\'s web_search_preview tool. Use this to find current information, news, or facts not in training data. Returns search results with titles, snippets, and URLs.'
• Document output schema explicitly. Specify that response contains 'content' array with 'type' and 'text' fields. If OpenAI API returns structured results (URLs, snippets, sources), include those in the schema.
• Implement error classification: distinguish between retryable errors (timeout, rate limit) and user-fixable errors (invalid query). Return actionable guidance: 'Query too long (501 chars). Max 500 chars. Try shortening or splitting into multiple searches.'
• Consider renaming to 'search_web' to strengthen verb_noun convention and improve LLM intent recognition.