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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well-covered. The description adds valuable behavioral nuance: explains that counts are registered residents at the FIRST DAY of each quarter, so '2026Q2' is a 1 April snapshot, not a quarterly average. Also notes it's keyless (no auth needed). This contextualizes the tool's semantics beyond the annotations.

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 dense but efficient — roughly four sentences covering purpose, source, trigger phrases, and a semantic caveat. It front-loads the core purpose and data source. Could trim the quoted query phrases slightly but each earns its place for agent routing.

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 zero-required-param, single-optional-param tool with strong annotations and 100% schema coverage, the description is quite complete. It covers source, purpose, trigger conditions, temporal semantics, and alternative tools. The only gap is not describing the output/return format of the trend data, though no output schema exists to compensate — but given the tool's simplicity, this is acceptable.

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 coverage is 100% and the only parameter (quarters) has a clear description in the schema itself ('How many recent quarters to include in the trend, 1-40, default 8'). The description adds a small but useful detail that 'the headline figure is always the newest', clarifying the relationship between the trend parameter and the main output. 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 states a specific verb+resource ('Denmark's total population in ONE call, from Statistics Denmark, table FOLK1A') and clearly distinguishes itself from siblings (list_tables/get_data for breakdowns). It's unambiguous about what it returns and the source.

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?

Explicitly lists query phrases that should trigger this tool ('PREFER for...'), and explicitly says to use list_tables/get_data for breakdowns by region, age, sex, or marital status. This gives the agent clear when-to-use and when-not-to-use guidance.

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