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

Annotations already mark this as read-only, idempotent, non-destructive, and closed-world. Beyond that, the description adds auditability, a formula-level explanation, an output field list, a direct REST fallback endpoint, and an explicit warning not to guess another /api path.

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 front-loaded with usage guidance and organized into labeled sections, which makes it easy to scan. It is somewhat overlong because it re-lists outputs that are already covered by the output schema and repeats parameter examples.

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 single-country working-day count, the definition covers when to use it, when not to use it, inputs, outputs, calculation behavior, fallback endpoint, and documentation. Nothing critical for correct invocation appears to be 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%, so the schema already documents all four parameters. The description lists the inputs and includes a full JSON example, but this largely repeats the schema rather than adding new parameter meaning.

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: counting auditable France working and non-working dates in a range. It clearly distinguishes this France-scoped count from the many add_* and check_* sibling tools by naming the country scope and the calculation action.

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?

It gives explicit positive guidance ('use this when you need an auditable France working-day count') and negative guidance about calendars that are not inferred. It also says to call the tool directly rather than answer from memory or stop at discovery. It does not explicitly name the sibling alternatives, so this is strong but not complete.

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