estimate_wait_time

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

No annotations are provided, so the description bears the full burden of behavioral disclosure. It mentions the inputs to the calculation but does not state whether the operation is read-only, what the return value looks like, how optional parameters affect the estimate, or how missing data is handled.

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?

The description is a single efficient sentence with no filler. It is front-loaded with the purpose and calculation inputs. Slightly more structure or explanation could improve it, but it is appropriately concise for a simple tool.

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 annotations, no output schema, and 0% parameter description coverage, the description is too sparse for an agent to call the tool correctly with confidence. It omits the meaning of optional parameters, the output format, and any prerequisites or limitations.

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 0%, so the description must compensate by explaining parameters. It references '실시간 가능대수' and '과거 출차 통계' as data sources, but it does not map these to parking_lot_id, target_datetime, or current_queue_count, nor does it clarify their roles in the calculation.

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 uses a specific verb, '계산합니다' (calculates), with a clear resource, '예상 대기시간' (estimated waiting time), and even states the data basis: real-time available spaces and past departure statistics. This clearly distinguishes it from sibling tools that search, find, get, recommend, or analyze congestion.

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 implies usage when an estimate of waiting time is needed, but it does not explicitly state when to prefer this tool over alternatives like analyze_parking_congestion. There is no exclusions or alternative guidance, so the usage context is only implicit.

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