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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, so the safety profile is covered. The description adds genuinely new behavioral context: the source is reported contracts from MOLIT, the values are medians rather than averages, and the window is capped at 12 months — all of which affect interpretation and answer confidence.

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 sentences, front-loaded with the metrics and time window, second sentence immediately routing to the question type it answers. Slightly dense phrasing ("Month by month median ... for each of the most recent months (up to 12)") repeats the recency idea, but nothing is wasted.

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?

With no output schema and no annotations gap, the description does the important work of telling the agent what series comes back (median rent, deposit, jeonse deposit per month) and where it comes from. Minor omissions — currency unit, whether deposits are in 만원, and handling of months with no reported contracts — keep it from a 5.

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% and the `area` parameter description already enumerates accepted granularities (country, province, district, Korean script). The description only restates "an area of South Korea" and adds nothing about the optional `province` disambiguator, so baseline 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?

Names a specific resource (month-by-month median apartment rent, deposit and jeonse deposit for an area of South Korea) with data provenance (MOLIT reported contracts) and a cap of 12 recent months. It implicitly separates itself from siblings like housing_median (single snapshot) and housing_compare (cross-area comparison) via the trend framing, but never names those siblings outright.

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?

"Fits questions about whether rent is rising or falling in an area" gives an explicit usage condition that maps a question shape to this tool. It stops short of stating when NOT to use it or which sibling to pick instead (housing_compare vs. housing_median vs. housing_report), which is the main remaining gap.

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