analyze_parking_congestion

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

With no annotations provided, the description carries the full disclosure burden. It does add one genuinely useful behavioral trait: it instructs the agent to surface availability_summary, distance_summary, and congestion_score in the reply, which tells the caller how to handle the output. However, it does not disclose whether the operation is read-only, how the scores are derived, what 'congested or high wait probability' means operationally, or what happens when no lots match the criteria.

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 sentences with no filler. The first sentence front-loads the core purpose and filtering criterion; the second sentence earns its place by telling the agent which result fields to include in the user-facing answer. Every clause carries information.

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?

This is a 7-parameter tool with 0% schema coverage, no output schema, and no annotations, yet the description is only two sentences. It does not explain how latitude/longitude, destination, radius_m, or target_hour shape the analysis, nor what ranges or defaults govern them, nor how to interpret the three result fields. For a tool with this complexity and zero structured support, the description leaves substantial gaps.

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 for all seven parameters, but it only implicitly references day_type through '평일/주말' (weekday/weekend). The remaining parameters (limit, latitude, longitude, radius_m, destination, target_hour) are entirely unexplained in both schema and description. The minimal partial coverage of day_type is the only semantic contribution.

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 (analyze) applied to a concrete resource (parking lots with congestion/high waiting probability) with a clear criterion (weekday/weekend). Naming the three output fields (availability_summary, distance_summary, congestion_score) sharpens what the tool produces. It is distinguishable from sibling tools like search_destination and find_parking_lots, though its boundary with estimate_wait_time and recommend_parking is not explicitly drawn.

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?

No explicit when-to-use or when-not-to-use guidance is given, and no alternatives are mentioned despite several overlapping siblings (recommend_parking, estimate_wait_time, find_parking_lots). The intended usage is only implied by the description's wording, leaving the agent to infer when congestion analysis is the right choice versus a single-lot wait estimate or a generic recommendation.

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