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

Annotations already declare the operation read-only, idempotent, non-destructive, and closed-world, so safety is covered. The description adds provenance ('reported contracts (MOLIT)') and the metrics returned, but omits important behavioral context such as the reporting period, data recency, or how missing contracts are handled.

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 tight sentences, front-loaded with the metrics and scope, followed by the use case. Every sentence carries information an agent needs.

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 five parameters, full schema coverage, and annotations covering safety, the description is nearly complete for selecting and invoking the tool. The main gap is the absence of timeframe or data-freshness context, which matters for interpreting housing price comparisons.

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 100%, with detailed area examples, optional province disambiguation, and enum defaults already documented. The description adds no parameter-level meaning beyond the schema, so the baseline of 3 applies.

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 comparison operation (median monthly rent, jeonse deposit, apartment sale price side by side) for two Korean areas, with the data source (MOLIT reported contracts). The two-area comparison scope implicitly distinguishes it from single-area siblings like housing_median and time-series housing_trend.

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 'fits choosing between two districts or cities,' giving a clear use context. It does not name alternatives such as housing_median for a single area or state when not to use it, so it falls short of full routing guidance.

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