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

With no annotations, the description carries full burden. It discloses the return state (keine_steuer | berechenbar | sondermodell), the data fields provided, and that rent computation only works for computable cities. Missing explicit error-handling details and a statement of read-only nature, but 'look up' implies it. No contradiction with annotations.

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 three sentences, front-loaded with purpose, then optional parameter, then return state. No wasted words; each sentence adds distinct information.

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 no output schema and moderate complexity, the description covers purpose, parameters, and return state. It could specify exact response structure or error behavior, but it's sufficiently complete for a lookup tool with this scope and sibling context.

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 detailed descriptions for both `city` and `monthly_rent`. The description reinforces that monthly_rent computes the annual tax and ties to net cold rent, but adds minimal new meaning beyond the schema. Baseline 3 is appropriate.

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 clearly states the tool looks up the German second-home tax for a city, listing specific outputs (levy status, rate, basis, rank, official source, Stand). The verb 'look up' is specific and the resource is well-defined, distinguishing it from sibling tools like by_state, ranking, and changes.

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 implies usage when you need city-level tax details and mentions the optional monthly rent to compute annual tax. It doesn't explicitly name alternatives or exclusions, but sibling tool names make the scope clear (e.g., by_state, ranking). Clear context but no explicit when-not-to-use guidance.

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