Analyze where a product ranks in its category — price positioning (budget/mid/premium/luxury), rating comparison, cheaper and pricier alternatives.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Product to analyze (required) | |
| country | No | Country code (default: DE) | |
| category | No | Category to compare against (auto-derived if not set) |
Changes observed during successful MCP inspections.
Input schema / additionalPropertiesAdded value: +falseDoes the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses output facets (budget/mid/premium/luxury, rating comparison, alternatives) but doesn't mention read-only status, data freshness, or any limitations. Some behavioral context is given, but key aspects remain unspecified.
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?
A single, well-structured sentence that front-loads the core purpose and follows with specific examples via em-dash. Every word contributes value; no wasted content.
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?
Description outlines the main output categories and mentions the auto-derived category (via schema parameter). Though no output schema exists, the description gives enough for a simple query but lacks exhaustive structure or edge cases.
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?
Input schema has 100% coverage for all three parameters (query, country, category), so the schema handles parameter meaning. The description adds no additional parameter details, leaving baseline of 3.
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?
Description uses the specific verb 'Analyze' and a clear resource ('where a product ranks in its category'), then enumerates concrete outputs (price positioning, rating comparison, cheaper/pricier alternatives). This distinguishes it from sibling tools like compare_prices or product_search.
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 clearly conveys the use case (analyzing a product's market positioning) without explicitly naming alternatives or exclusions. The context is evident, but there's no direct comparison to sibling tools like competitor_pricing or bestseller_list.
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.