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

Annotations already cover readOnly, idempotent, and non-destructive hints. The description adds that filtering is based on marketing-authorisation date and explains the date-window concept, which is useful behavioral context beyond the schema.

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 concise and front-loaded, with a clear purpose statement and relevant example questions. The examples add value without bloating the text.

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 5 optional parameters, 100% schema coverage, and strong annotations, the description adequately explains what the tool returns and when to use it. It lacks explicit return-format details but that is not critical here.

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% with parameter descriptions. The description adds the semantic that 'month' overrides from/to and clarifies the date-window concept tied to marketing-authorisation date, which goes beyond the raw 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 explicitly states the tool lists new medicines authorised by the EMA within a date window, and enumerates the returned fields (brand name, INN, therapeutic area, indication, MAH, date, EPAR link). It clearly distinguishes from siblings like ema_chmp_opinions (opinions) and ema_medicine (specific drug details).

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 concrete example questions ('which drugs did the EMA approve in July 2026') and notes filtering on marketing-authorisation date. It does not explicitly mention exclusions or alternative tools, but the context makes intended usage clear.

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