This is a web scraping toolkit with 18 tools that exhibit consistent patterns but significant gaps in quality. All tools follow a verb_noun naming convention (amazon_bestsellers, google_search, scrape_as_markdown) which is good. However, the server has critical issues: (1) Descriptions are present but vary in quality, some like 'Scrape Amazon Bestsellers list with automatic parsing' (54 chars) are on the short side; (2) Input schemas are visible and use Zod for type definition, which is solid, but parameter descriptions are sometimes generic ('Geo location' vs 'Geographic location as country code or ZIP code'); (3) Output schemas are NOT documented anywhere, tools return JSON text without declaring the structure, making it impossible for LLMs to plan chaining; (4) No error handling guidance, tools call external APIs with no visible retry logic, timeout handling, or recovery guidance; (5) No per-tool validation or error categorization. The codebase shows basic schema construction (e.g., amazon-pricing-tool.ts registers inputSchema with Zod) but omits output documentation entirely. Most tools are READ_ONLY with no destructive hints needed, which is appropriate. Tool names are mostly clear (search, scrape, get patterns work well), but lack context about what data each returns, e.g., both 'google_search' and 'bing_search' exist but descriptions don't clarify when to use one vs the other. Composition is weak: no evidence of chaining support or how results from one tool feed into another. Overall, this lands in 'Fair/C range' due to present but incomplete descriptions, missing output schemas, and no error recovery guidance.

• Document output schemas for all 18 tools. For each tool, publish a schema showing the fields in the 'data' object returned. For example, amazon_product should declare: {type: 'object', properties: {asin: {type: 'string'}, title: {type: 'string'}, price: {type: 'number'}, rating: {type: 'number'}, ...}}. This enables LLMs to extract relevant fields and plan chaining.
• Enhance parameter descriptions with specific guidance. Replace 'Geo location' with 'Geographic location: US ZIP code (e.g., "10001"), country code (e.g., "US"), or city name (e.g., "New York")'. Replace 'Enable JavaScript rendering' with 'Set to true if the page requires JavaScript to load dynamic content (e.g., infinite scroll, lazy-loaded images). Increases latency by ~2-5 seconds. Default false for faster results.'
• Add error handling with actionable recovery steps. Wrap sapiClient.scrape() calls in try/catch, categorize errors (timeout, rate-limit, page-not-found, invalid-param, server-error), and return structured error responses guiding the LLM. Example: {error: 'rate_limit_exceeded', message: 'Too many requests. Try again in 60 seconds or use a different geo/domain.', retryable: true}.
• Clarify tool selection by adding 'Use this tool when...' guidance in descriptions. E.g., google_search: 'General web search with traditional 10 blue links. Use for news, facts, and documentation.' google_ai_mode: 'AI-generated summaries with synthesized answers. Use for complex questions requiring analysis vs. link browsing.'
• Document pagination behavior for tools accepting pageFrom. Specify: 'pageFrom is 1-indexed (start=1 for first page). Results are capped at [X] items per page. Total count is not returned; stop when results < [X] or an error occurs.'