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get_bicycle_detections

Retrieve bicycle traffic counts from city counting stations for a specified counter ID and time period.

Instructions

Get bicycle traffic detection data from counting stations.

Args:
    id: Counter ID to get detections for
    from_date: Start date in ISO format (e.g. "2024-01-01T00:00:00Z")
    to_date: End date in ISO format (e.g. "2024-01-31T23:59:59Z")
    aggregate: Whether to aggregate the results

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
to_dateNo
aggregateNo
from_dateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Get bicycle traffic detection data,' without stating whether it is read-only, whether aggregate changes response shape, or any side effects. Important behaviors like date inclusivity, pagination, or handling of null id are omitted.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with a clear first sentence and a structured Args listing. Every line adds value and there is no filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 4 optional parameters, no annotations, and an output schema. The description covers the core action and parameter basics but lacks richer context such as selecting between this and get_bicycle_counters, behavior when aggregate is true, or edge cases with null values. The existence of an output schema reduces the need to explain return values, yet the description still feels incomplete for a full understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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. It provides short explanations for each parameter (id, from_date, to_date, aggregate) with date format examples, but these are minimal. It does not clarify optionality, what 'aggregate' actually does, or the meaning of null id, so it only partially compensates for the schema gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get bicycle traffic detection data from counting stations,' which is a specific verb+resource. It distinguishes from sibling tools like get_bicycle_counters by focusing on detection data rather than the counters themselves.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by listing parameters (id, from_date, to_date, aggregate) but does not explicitly state when to use this tool versus alternatives like get_bicycle_counters. There are no exclusion criteria or alternative tool references, so the guidance is only implicit.

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

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