list_seoul_recent_updates

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

With no annotations provided, the description carries the full disclosure burden and does well: it reveals the descending sort behavior by DATA_LT_NM and, more valuably, the caveat that results exceeding 1,000 rows are only sample-sorted and a note announces this. This is genuine behavioral insight beyond the schema. Minor gaps remain around result shape and the note's exact placement.

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?

Three tight sentences: core action and sort order first, filtering options plus use case second, and the sample-sort caveat last. No filler, no repetition of schema content — every sentence earns its place and the most important action is front-loaded.

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 there is no output schema and no annotations, the description covers the essentials an agent needs to decide and invoke: purpose, sort semantics, filter capability, use case, and the 1,000-record sampling caveat. It falls just short of fully complete because it never describes the shape of returned items or how the note surfaces, which matters more without an output schema.

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 schema already documents all five parameters (limit, apiOnly, keyword, orgName, division) with defaults and examples. The description adds modest framing by grouping the filters (keyword/org/division) and enumerating division values (본청·산하기관·자치구), but it does not fundamentally extend parameter meaning.

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 specific verb and resource ('최근 갱신된 서울시 데이터셋을... 조회합니다') with an explicit sort criterion (DATA_LT_NM 내림차순). The recency-focused scope and the 'actively managed APIs' use case set it apart from generic search or detail siblings, though it never names a sibling directly.

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 gives a clear contextual trigger: '요즘 활발히 관리되는 API를 바로 찾을 때 유용합니다' (useful when looking for actively-managed APIs). It implies this tool is for recency-driven discovery rather than general purpose search, but it does not state exclusions or explicitly route to alternatives like search_seoul_datasets.

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