recommend_seoul_apis_for_idea

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

With no annotations present, the description discloses the core behavior: automatic keyword search and scoring over the catalog, then returning top results. This goes beyond a bare action statement, though it does not describe side effects or limitations; the read/recommend nature is still reasonably transparent.

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 short sentences with no filler; the main action is front-loaded and the scoring/return behavior is stated concisely in the second sentence. Every sentence earns its place.

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?

The description is adequate for a recommendation tool but leaves gaps: no output schema is provided and the description does not clarify the returned result shape, sorting order, or empty-result behavior. The detailed parameter schema compensates partially, but an agent still does not know exactly what the returned 'top results' look like.

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%, and every parameter already has a meaningful description, including examples where useful. The free-text description adds no extra parameter-level semantics beyond mentioning keyword search/scoring, so the baseline score 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?

The description states a specific action ('recommends suitable API candidates') against a named resource (Seoul open data catalog), and clearly centers on natural-language idea input. It does not explicitly contrast with sibling tools like search_seoul_datasets, so it falls short of a 5.

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 opening phrase '자연어로 아이디어를 설명하면' implies the intended use case: use this when the user has an idea rather than a precise search query. However, it gives no explicit when-not-to-use guidance or mention of alternatives such as search_seoul_datasets or refine_seoul_recommendations, leaving routing partially implicit.

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