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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds that figures are 'asking price' stats and that no filtering or listing behavior is involved, but it does not clarify data coverage or aggregation behavior beyond that.

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 two short sentences with the key output front-loaded. The bilingual repetition is acceptable and adds no real bulk.

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 simple read-only stats tool with no output schema, the description provides the main return concept but leaves the transaction parameter undocumented and does not state whether inputs are optional or how location scoping works. Enough for basic selection, but not fully complete for invocation.

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 description coverage is 0%, so the description must carry parameter meaning. It explains city/neighborhood scoping but does not explain the transaction parameter (sale vs. rent) and mentions 'property type' even though no such parameter exists. This is only partial compensation for the schema gap.

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 states a clear resource and action: computing average and median asking price per m² for a city/neighborhood. It is distinguishable from siblings like search_properties or get_property. However, the phrase 'property type' is not represented in the schema, which introduces slight ambiguity.

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 use when aggregated price-per-m² statistics are needed, and siblings make it distinct from property search or inquiry tools. No explicit when-to-use or when-not-to-use guidance is given, but context makes the primary use case inferable.

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