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

Beyond the read-only/idempotent annotations, the description discloses critical behavior: the dataset is frozen through 2023-W47, is not live surveillance, and requires no auth. It also names the data source and license, which is exactly the kind of context annotations do not provide.

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 yet information-dense, front-loading the core function before adding filter options, temporal scope, source, license, and auth status. Every sentence earns its place with no filler or redundancy.

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 output schema and annotations, the description covers everything an agent needs to select and call this tool: data content, filters, temporal limitation, source, license, and auth requirements. No critical gap remains that would cause misinvocation.

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 parameters are already fully documented. The description mirrors the indicator enum and country filter in prose but adds no new parameter-level semantics beyond what the schema provides, matching 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?

States a specific verb and resource: getting historical ECDC COVID-19 hospital/ICU occupancy and weekly admission rates. It names the exact metrics, geography, and time coverage, distinguishing it from sibling ECDC tools like cases_deaths and testing_rate without needing to infer from the schema.

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 gives clear context for when to use this tool: when historical ECDC hospital/ICU occupancy or admission-rate data by country is needed. It does not explicitly name alternatives or state when not to use it, but the subject-matter scope is unambiguous enough for an agent to route correctly.

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