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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description still adds real value by disclosing the data source ('official notices') and that only recently completed months are counted — a non-obvious temporal constraint. It stops short of describing result shape or ordering.

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?

Two dense sentences with the subject and granularities front-loaded, followed by parameter behavior. The inline enum mapping is slightly repetitive but earns its place because the schema leaves that enum undocumented.

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, so the description is the only place to explain what comes back, and it only says 'figures' — not whether these are counts of opened proceedings, per-period values, or how the dimension/name selection reshapes the response. The parameter and scope coverage is solid, but the return-value gap is meaningful for a statistics tool.

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 only 33%: `dimension` has no schema description and `months` only carries a default and bounds. The description compensates by mapping each enum value to its meaning (monat/bundesland/branche) and by defining `months` as the count of recent completed months, plus clarifying that `name` narrows to a single state or sector.

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 names a specific resource (corporate insolvency figures for Germany from official notices) and its three granularities, so an agent knows exactly what data it returns. It does not explicitly contrast itself with siblings like check_company or company_notices, but the resource is distinct enough that confusion is unlikely.

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?

Usage is only implied: the agent can infer it should call this to obtain aggregate insolvency statistics rather than company-level data. There is no explicit when-to-use/when-not statement and no mention of prerequisites or the sibling tools that would be preferred for per-company lookups.

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