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lacausecrypto

mcp-new-caledonia

nc_get_job_seeker_stats

Retrieve job seeker statistics in New Caledonia by year, province, and grouping criteria like age, diploma, or sought profession.

Instructions

Get statistics about job seekers in New Caledonia by various criteria

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoYear to query
group_byNoHow to group resultsprovince
provinceNoFilter by province
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'Get statistics' — it does not state that the operation is read-only, what the response format looks like, whether parameters are required (they are all optional), what happens with no input, or any side effects. For a statistics retrieval tool, this is a significant lack of transparency, leaving the agent to guess the output structure and invocation behavior.

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

Conciseness3/5

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

The description is a single concise sentence that is front-loaded with the core action. It contains no wasted words, which is good, but it is too brief to be considered well-structured for a tool with multiple optional parameters and grouping semantics. It lacks the detail that could be conveyed in a few more sentences without becoming verbose. The conciseness is acceptable but not exemplary.

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

Completeness2/5

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

There is no output schema and no annotations, so the description must provide sufficient context for an agent to call the tool correctly. It does not mention what the returned statistics represent, how the group_by options affect results, or the effect of omitting all parameters. While the schema explains parameters, the absence of response details and usage context leaves the tool incomplete for practical use.

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 coverage is 100%, so the schema already documents all three parameters (year, group_by, province) with descriptions and enums. The description adds only the vague 'by various criteria', which does not provide additional meaning beyond what the schema already offers. Baseline 3 is appropriate since the schema does the heavy lifting, and the description offers minimal extra value.

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 the verb 'Get', resource 'statistics about job seekers', and location 'New Caledonia'. It distinguishes itself from siblings by topic — no other tool covers job seeker statistics, and it is clearly differentiated from population stats, vehicle stats, etc. The 'by various criteria' hints at filtering/grouping but the core purpose is unambiguous.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention any sibling tools or conditions under which this tool should be preferred. The phrase 'by various criteria' is vague and does not explain the scenarios for using group_by or province filters. No exclusions or alternative recommendations are given.

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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