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

With no annotations, the description carries the full burden and does well: it names the data source (MOLIT reported apartment sales), discloses that cancelled deals are excluded, states the price ($0.0045 USDC via x402 on Base or Solana), and notes that the call is paid. Missing operational traits such as rate limits, caching/freshness lag, and failure modes beyond the 400-invalid-region case keep it short of a 5.

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?

Front-loads the usage directive, then layers Data / Input / Output / Example / Price in a scannable structure with no filler sentences. The Input line duplicates the schema verbatim and the example is somewhat redundant, costing it the top mark.

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 paid endpoint with no output schema, the description usefully enumerates the return shape (count, median/avg/min/max, KRW and USD, size-class breakdown, top complexes) and the data provenance. It is close to complete; only error behavior other than the 400 case and the billing/retry semantics are unaddressed.

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%, so the baseline is 3; the description mostly restates the schema (5-digit LAWD_CD, YYYYMM) but adds a concrete invocation example '?region=11680&month=202609' that shows both required params combined. That is marginal added value over the schema's own examples, not new semantics.

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 resource (Korea apartment price summary for a district-month) with the concrete aggregates produced (count, median/avg/min/max, price per m²/pyeong). It explicitly contrasts with the raw-trades sibling ('a quick housing-market snapshot ... instead of raw trades'), so an agent can distinguish it from kr_apartment_trades without opening either schema.

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?

Opens with a clear routing rule: 'Use when you need a quick housing-market snapshot ... instead of raw trades,' which effectively names the alternative. It lacks explicit preconditions or exclusions (e.g. what to do for non-apartment housing types or regions outside the MOLIT feed), so it is clear context rather than a full when/when-not matrix.

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