Relevés de la rubrique Apprendre de Meridal

Notes des modèles à un test

classement_d_un_test

Read-onlyIdempotent

Rend les notes des modèles à un test (Artificial Analysis, GPQA, SWE-bench, Arena…), de la plus haute à la plus basse, chaque note avec sa source, son adresse et sa date, et le test avec ce qu'il mesure et ses limites connues. Sans test précisé, liste les tests disponibles.

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": "classement_d_un_test"
  }
}

Input Schema

Name	Required	Description	Default
`test`	No	Un morceau de l'identifiant ou du nom du test : « gpqa », « swe_bench », « arena ». Vide : la liste des tests.
`limite`	No	Nombre maximal de notes rendues (10 par défaut)

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 15, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and non-open-world, so the safety profile is covered. The description adds useful behavioral detail beyond that: results are sorted highest-to-lowest, each score carries source, address and date, and test metadata includes what it measures plus known limits.

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 purpose is front-loaded in the first clause, and the whole definition is two sentences with no filler. The first sentence is dense with return-field information, but every element serves selection or invocation.

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

Completeness4/5

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

With only two optional parameters, no output schema, and annotations covering safety, the description supplies the missing return-format information (sort order, source/address/date per score, test limits). Nothing essential to calling it correctly is absent; pagination or result-size behavior beyond the limite default is the only minor gap.

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 100%, so both parameters are already documented, including the 'Vide : la liste des tests' behavior and the default of 10 for limite. The description only restates the empty-test case and adds no format or matching detail beyond what the schema provides, so the baseline 3 applies.

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?

States a specific verb ('Rend') and resource ('les notes des modèles à un test'), names concrete example tests (Artificial Analysis, GPQA, SWE-bench, Arena), and describes the ordering and the fields returned. The resource is plainly distinct from siblings like prix_du_modele or comparer_les_abonnements, though no sibling is named explicitly, which keeps it just short of a 5.

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

Usage Guidelines4/5

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

The final sentence gives concrete usage context: with no test specified it returns the list of available tests, which tells the agent how to discover valid inputs. It does not, however, mention when to prefer or avoid this tool versus any alternative, so it stops at clear context without exclusions.

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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