Statistics Finland — Population of Finland

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds value beyond these: it discloses that 'No API key required — official Finnish government open data (CC BY 4.0)' and provides an example of the latest figure (5,652,881 persons at end of 2025). It also clarifies the annual snapshot date (31 December), which is behavioral context not in 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 five sentences, each earning its place: purpose, historical range, example figure, source authority, and licensing/auth. It is front-loaded with the main purpose. It could be slightly tighter (e.g., merging the authority and licensing sentences), but there is no redundant fluff.

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 simple read-only tool with two optional parameters and an output schema present, the description covers everything an agent needs: the exact country and data source, the time range, the output granularity, an example value, and authentication requirements. No critical context is missing.

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% — both 'sex' and 'years' have thorough descriptions including defaults, ranges, and explanations. The description paraphrases these ('total, male, or female', 'up to 276 years back to 1750') but does not add new semantic meaning beyond the schema. Baseline 3 is appropriate when the schema carries the parameter documentation burden.

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 opens with a precise verb and scope: 'Get the historical and current population of Finland on 31 December each year.' It specifies the exact metric (population), the country (Finland), the time granularity (annual, year-end), and the historical reach (up to 276 years back to 1750). This clearly distinguishes it from siblings like abs.demographics.population (Australia) and census.data.population.

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 strong contextual clues about when to use it: it identifies the data source as 'Statistics Finland population register' and the geography as Finland, implicitly distinguishing it from national statistics tools for other countries. However, it does not explicitly state 'for other countries use X' or exclude alternatives, so it falls short of explicit alternatives guidance.

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