[Premium Data] Compare product prices across e-commerce platforms using Google Shopping and direct URL monitoring. Args: product_name: Product name to search product_urls: Direct product page URLs to check max_results: Max results (default 20)
| Name | Required | Description | Default |
|---|---|---|---|
| max_results | No | ||
| product_name | No | ||
| product_urls | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds that it uses Google Shopping and URL monitoring, which is useful context but does not explain potential errors, data freshness, or limitations. It does not contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: one sentence stating the purpose plus a compact list of parameters with short descriptions. Every sentence adds value, and the main action is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, no output schema, and reasonably informative annotations, the description covers the essentials but lacks details about the return format, real-time nature, or any constraints. It is adequate but not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, but the tool description provides short yet meaningful descriptions for all 3 parameters: 'Product name to search', 'Direct product page URLs to check', and 'Max results (default 20)'. This compensates for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'compare', the resource 'product prices', and the scope 'across e-commerce platforms using Google Shopping and direct URL monitoring'. It distinguishes itself from sibling tools focused on other domains like crypto or finance prices.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used for comparing product prices but does not provide explicit guidance on when to use it versus alternatives, nor does it mention when not to use it or list alternatives like 'search_amazon_products'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have overlapping functionality across categories (e.g., multiple search_arxiv, search_google_scholar, real estate tools, DNS/WHOIS checks). An agent would struggle to differentiate between similar tools from different categories, leading to ambiguity.
Tools follow a 'category__verb_noun' pattern mostly, but verbs vary (get, search, screen, check, etc.) and some categories use different orders (e.g., 'get_repo_stats' vs 'search_repos'). The consistency is acceptable but not uniform across the entire set.
With 152 tools, the server is excessively large for a single MCP server. While it aims to be an all-in-one gateway, the sheer number overwhelms the agent and likely exceeds practical limits for coherent selection.
The server covers a wide range of domains (finance, real estate, news, developer tools, etc.) but has notable gaps (e.g., social media APIs, CRM tools). Coverage is broad but not exhaustive, and some niche areas (e.g., global stock exchanges) are over-represented.