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

Annotations already declare readOnly, idempotent, non-destructive and openWorld, so the safety profile is covered. The description adds genuinely new context: 'live' data, no rate limit, and the precise definition of 'urgent' (deadline ≤ 14 days), which an agent could not infer from the annotations alone.

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?

Front-loaded with the core behaviour and field list, followed by usage context and examples. Every sentence earns its place, though the example-question block is a little verbose for a no-parameter count tool.

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?

There is no output schema, and the description compensates by listing the key return fields and clarifying the semantics of the 'urgent' bucket and data freshness. For a parameterless statistics endpoint, an agent has everything needed to select and call it.

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?

With zero parameters the baseline is 4. The description goes slightly beyond by naming the key output fields (open_count, urgent_count, etc.), which is a bonus rather than a requirement for a parameterless tool.

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 (returns counts) and resource (Vergabe notices) and enumerates exactly what is counted: open, urgent, awarded, total, plus URL health and model name. This clearly distinguishes it from siblings like vergabe_liste or vergabe_suche, which return notices rather than aggregate statistics.

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?

Explicitly says it is 'suited to questions about database size and current tender counts' and gives three concrete example questions, so an agent knows the triggering intent. It does not, however, name alternative siblings (e.g. vergabe_liste) or state when NOT to use it, so the routing guidance is implicit rather than exclusionary.

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