Polish Academic MCP

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the return format ('Returns JSON with total_count and a list of items including DOI, description, authors, and citation'), which is valuable. However, it doesn't mention pagination behavior (implied by parameters but not explained), rate limits, authentication requirements, or error handling, leaving gaps for a mutation-free search tool.

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 perfectly concise with two sentences: the first establishes purpose and context, the second provides key usage guidance and output format. Every word earns its place, and the most important information (what it does and how to use it) 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?

For a search tool with no annotations, 100% schema coverage, but no output schema, the description does well by explaining the return format. It covers the essential context (what it searches, what it returns, a key usage tip). The main gap is lack of explicit sibling differentiation, but given the schema handles parameters well, this is reasonably complete.

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 description coverage is 100%, so the schema already fully documents all 4 parameters. The description adds marginal value by reinforcing the query parameter's special value ('Use query='*' to browse all available datasets'), but doesn't provide additional semantic context beyond what's in the schema descriptions. This meets the baseline for high schema coverage.

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 ('Search') and resource ('research datasets in RODBuK'), specifies the repository's scope ('Krakow inter-university open research data repository'), and distinguishes it from siblings by mentioning it's powered by Harvard Dataverse, which no other sibling tool references. This provides specific differentiation beyond just the search functionality.

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 clear context for when to use this tool ('Search research datasets in RODBuK') and includes a specific usage tip ('Use query='*' to browse all available datasets'). However, it doesn't explicitly state when not to use it or name alternatives among the many sibling search tools, which would be needed for a perfect score.

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