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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds useful behavioral details: row cap (1-1000), default limit (200), return format (one row per data point with dimension code+label and value), data source, and no-auth requirement. These go beyond annotations without contradicting them, though it does not discuss error handling or edge cases.

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 compact and front-loaded with the core operation. Each sentence earns its place: main action, return format, row cap, and data source/auth. No redundant or filler 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?

For a read-only data-fetching tool with a rich input schema, output schema, and safety annotations, the description covers the key operational constraints (limits, defaults, selection capabilities, source, auth). It is complete enough for an agent to call correctly, though it could optionally mention the prerequisite dataset_search step for cube_code, which is left to the schema.

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 input schema already thoroughly documents all parameters, including selection syntax (single, comma lists, ranges, lastN, wildcards). The description largely restates the schema content, adding little new meaning. It also slightly conflates the source of cube_code (schema says dataset_search, description implies dataset_metadata), so its added value is marginal and slightly imprecise.

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 states a specific verb and resource: "Fetch data rows from one DATAcube table". It clearly distinguishes the data-fetching tool from sibling reference tools like dataset_metadata and dataset_search by focusing on retrieving data rows, not metadata. The mention of cube_code + selections and the return format further pin down its purpose.

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 by pointing to slovakia-statistics.dataset_metadata as the source for selections, implying a necessary prerequisite step. It does not explicitly state when not to use this tool versus alternatives, but the sibling structure makes the intent clear. No explicit exclusions or alternatives are named, so it stops short of a 5.

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