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 (제주관광빅데이터플랫폼, SKT mobile network monthly aggregation), flags that it is not real-time, and discloses the no-region fallback plus the no_data error state. It does not cover pagination limits or the exact response shape, which is the remaining gap.

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-loaded with what the tool returns, then the source/timing caveat, then the two calling behaviors. Every sentence carries information, though the source attribution sentence is dense and could be tightened.

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 single-parameter tool with no output schema, the description covers everything an agent needs: data provenance, temporal granularity and its limitation, default scoping when region is omitted, notation tolerance, and the error-handling instruction for no_data.

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 region parameter is already documented, but the description adds real meaning beyond the schema: omitting region returns the latest month's full 읍면동 list, and both 행정동 (용담2동) and 법정동 (용담이동) notations are auto-mapped. That last point prevents a whole class of failed calls.

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 verb and resource: monthly visitor statistics by 제주 읍면동, split domestic/foreign with MoM and YoY comparisons. No sibling tool covers tourism statistics, so the agent can distinguish it immediately from get_site_stats, get_ad_stats, or get_price_stats.

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?

Gives clear usage context and an explicit when-not: because the data is monthly aggregation, it says to explain monthly patterns rather than 'it's crowded now', and it describes the no_data recovery path (re-query with available_regions). It stops short of naming which sibling to use for the real-time crowding question (e.g. find_quiet_spots).

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