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

Beyond the annotations (readOnly, idempotent, non-destructive), the description adds valuable behavioral context: data comes from listings, not notarized transactions; sub-districts are mapped to their parent district; if a location is not in the dataset, nothing is estimated. This fully discloses limitations and data provenance.

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 well-structured, with the core purpose front-loaded and each sentence contributing distinct value (data content, data source, scope, fallback behavior, and alternative tool). No redundancy or filler.

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 read-only market data tool with no output schema, the description is complete. It specifies what data is returned, the source, the mapping behavior, and when to use an alternative. An agent can call this tool correctly without additional 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%, so the schema already documents both parameters. The description adds extra meaning by explaining that sub-districts like Haidhausen, Solln, or Pasing are automatically mapped to their respective city district, and that 'München gesamt' gives city-wide values. This goes beyond the schema's basic description.

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 it delivers market data from Kopp Real Estate for a Munich district or the whole city, listing the specific metrics (offer price per sqm, rent, yield, multiplier) with date and source. It explicitly differentiates from sibling tools by noting it is not for individual property assessment and points to kopp_bewertung_anfragen.

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 explicit usage context: it is for aggregated market data, not individual property evaluation, and directly tells the agent to use kopp_bewertung_anfragen for personal assessments. It also clarifies the data basis (listings, not notarized prices) and that unknown locations are not estimated.

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