Kolada MCP Server

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

Annotations indicate read-only, non-destructive, and idempotent behavior, which the description doesn't contradict. The description adds value by specifying what the tool returns (statistics like min, max, mean, median, ranking, top and bottom municipalities) and its use case (benchmarking and comparisons), which goes beyond the annotations. However, it doesn't mention potential limitations like rate limits or authentication needs, though annotations cover some safety aspects.

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, stating the core functionality in the first sentence and adding context in the second. It uses two sentences efficiently without unnecessary details. However, it could be slightly more structured by explicitly separating purpose from usage, but it's still well-organized and to the point.

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 (6 parameters, no output schema) and rich annotations, the description is fairly complete. It explains what the tool does and its use case, but doesn't detail the output format or potential errors. With annotations covering safety and idempotency, and schema covering parameters, the description adds sufficient context, though it could benefit from mentioning the lack of an output schema or example outputs.

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 input schema has 100% description coverage, providing clear details for all parameters (e.g., kpi_id, year, gender, municipality_type, top_n, bottom_n). The description doesn't add any parameter-specific information beyond what's in the schema, such as explaining parameter interactions or default behaviors. With high schema coverage, the baseline is 3, as the schema does the heavy lifting.

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: analyzing a KPI across municipalities with statistics (min, max, mean, median) and ranking, showing top and bottom municipalities. It specifies the resource (KPI across municipalities) and the action (analyze with statistics and ranking). However, it doesn't explicitly differentiate from sibling tools like 'compare_kpis' or 'get_kpi_data', which might offer similar functionality, so it's not a perfect 5.

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 usage for benchmarking and comparisons, suggesting when to use it (for performance analysis across municipalities). However, it doesn't provide explicit guidance on when to choose this tool over alternatives like 'compare_kpis' or 'filter_municipalities_by_kpi', nor does it mention any exclusions or prerequisites. The guidance is implied rather than explicit.

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