Fiscal By Institution

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

Annotations already declare the tool read-only and idempotent, so the description does not need to repeat that. It adds meaningful behavior beyond annotations: the data starts in 2007, and empty results carry a `note` with guidance, which is valuable operational context for an agent.

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 every sentence earns its place: definition, use case, parameter guidance, and empty-result handling. It is front-loaded with the core purpose and contains 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?

For a read-only query tool with a rich annotation set and an output schema, this is nearly complete: it gives valid variable values, data range, an illustrative query, and empty-result behavior. The main gap is not mentioning how to discover valid `departement` values or when to prefer sibling tools like `fiscal_list_dimensions`.

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 0%, so the description must compensate. It enumerates the accepted values for `variable`, and the example 'IT spending of the Finanzdepartement since 2010?' gives practical meaning to `departement` and the year range parameters. It does not specify valid `departement` spellings, but it still adds substantial semantic value beyond the bare schema.

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 identifies the resource (federal spending data) and the unit of analysis (department/administrative unit), and the use case clarifies it is for cross-department comparisons. However, it lacks an explicit action verb like 'returns' or 'lists' and never names sibling tools to differentiate them, so it stops short of a 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 'Use case' line explicitly states when this tool is appropriate — comparing personnel, IT, or external-services spending across departments — and gives a concrete query example. It does not state exclusions or point to alternative sibling tools, so it misses the explicit when-not-to-use guidance that would earn a 5.

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