dutch-gov-mcp

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions dataset limitations ('free open dataset') but doesn't cover other critical aspects like read-only vs. mutation, authentication needs, rate limits, error handling, or response format. For a lookup tool with no annotation coverage, this is a significant gap in transparency.

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 and front-loaded, consisting of two sentences that efficiently convey the core purpose and key limitations. Every sentence adds value without redundancy, making it easy for an AI agent to parse quickly.

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's complexity (a lookup with one parameter) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and incomplete behavioral details, it lacks completeness for safe and effective use. It covers scope but misses operational context like permissions or errors.

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?

The schema description coverage is 100%, with the parameter 'kvk_number' fully documented in the schema. The description doesn't add any parameter-specific details beyond what the schema provides, such as examples or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 tool's purpose: 'Look up publicly filed financial statement metadata for a Dutch company.' It specifies the verb ('look up'), resource ('financial statement metadata'), and scope ('Dutch company'). However, it doesn't explicitly differentiate from sibling tools like 'lookup_company', which might handle different company data, leaving room for ambiguity.

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 provides some usage context: 'Only covers BV and NV companies in the free open dataset.' This implies when to use (for those company types in that dataset) but doesn't explicitly state when not to use or name alternatives. For example, it doesn't clarify if 'lookup_company' is for non-financial data, leaving usage guidance incomplete.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.