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list_datasets

Read-onlyIdempotent

Décrit le jeu de données ouvert 5G et son téléchargement CSV.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_datasets"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior3/5

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

The annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds one piece of behavior beyond that — that a CSV download reference is involved — which is useful given there is no output schema, but it does not say whether a URL, a file, or just metadata is returned.

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?

A single front-loaded sentence with no filler, which is appropriate for a no-argument tool. It is efficient but borders on under-specification rather than being genuinely tight, since the one sentence leaves the list-vs-describe ambiguity unresolved.

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 zero-parameter read-only tool with rich annotations, the description is close to sufficient, but with no output schema it should clarify what is returned (dataset metadata? a CSV link? multiple datasets?). The mismatch between the plural name and the singular description leaves a real gap an agent must guess at.

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

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters and the schema is empty with additionalProperties=false, so there is nothing for the description to disambiguate. Baseline 4 applies; no parameter-level meaning is missing.

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

Purpose3/5

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

"Décrit le jeu de données ouvert 5G et son téléchargement CSV" names a specific resource (the open 5G dataset) and a specific action (describing it plus its CSV download), but it conflicts with the tool name list_datasets, which implies enumerating multiple datasets. An agent cannot tell from the description whether it receives one dataset's metadata or a list.

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 when-to-use guidance is given, and neither sibling (compare_departments, get_department_5g) is mentioned, so the agent has no signal about how this differs from the department-level tools. The only implied usage is that this is the entry point for dataset discovery.

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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