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lacausecrypto

mcp-new-caledonia

nc_get_transport_modes

Get transport mode usage statistics from the 2019 census, filterable by province of New Caledonia.

Instructions

Get statistics on transport modes used by the population (from 2019 census)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
provinceNoFilter by province
Behavior2/5

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

No annotations are present, so the description carries the full burden of behavioral disclosure. It states the data source (census year) but does not disclose that this is a read-only operation, any limitations (e.g., missing data for certain provinces), or what the output looks like. For a 'get' tool with no annotations, more behavioral context is expected.

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

Conciseness4/5

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

The description is a single concise sentence, front-loaded with the principal action and resource. It is efficient with no filler. However, it is so minimal that it omits potentially useful details, but within the conciseness dimension, it is appropriately sized and well-structured.

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?

For a simple tool with one optional parameter and no output schema, the description provides the essential purpose and data source. However, it does not mention what statistics are returned (e.g., percentages, counts, breakup by mode), nor any caveats about data availability. With no annotations to supplement, the description is adequate but not complete.

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?

The schema has 100% description coverage for the single optional parameter 'province', which is described as 'Filter by province' with an enum. The description adds no additional meaning beyond the schema. Baseline score of 3 applies because the schema already documents the parameter adequately.

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

Purpose4/5

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

The description clearly states the verb ('Get') and resource ('statistics on transport modes used by the population'), and adds the data source (2019 census). It is unambiguous about the tool's purpose. It doesn't explicitly differentiate from sibling statistics tools (e.g., nc_get_population_stats, nc_get_vehicle_stats), but the resource is specific enough that an agent can infer the difference.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus similar statistical tools among the siblings. There is no mention of alternatives, exclusions, or conditions. The description only states what the tool does, leaving the agent to guess when it is the right choice.

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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