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outils

proposer_demande_rappel

PREMIERE etape d'une ecriture : prepare une demande de rappel (email + consentement explicite OBLIGATOIRES). Retourne un action_id a confirmer par l'utilisateur. Si email ou consentement manquent, retourne une elicitation (question a relayer au visiteur). Scope requis: leads.write.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
emailYes
projetNo
consentYesaccord explicite du visiteur (true requis)
messageNomessage du visiteur, sans donnees sensibles
telephoneNo
type_projetNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

With annotations that only say readOnly=false, destructive=false, the description carries the full burden of behavioral disclosure. It reveals mandatory email and explicit consent, the two-phase confirmation pattern, the elicitation fallback, and the required leads.write scope. There is no contradiction with annotations.

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 compact and front-loaded, covering purpose, requirements, return value, fallback behavior, and scope in three short sentences. Every sentence adds operational value with no filler.

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?

For a tool with no output schema and uninformative annotations, the description is unusually complete: mandatory inputs, return value, elicitation behavior, and required scope are all present. It stops just short of explicitly naming the confirmation sibling and leaves some optional field semantics to the schema.

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 only 29%, so the description needed to compensate. It adds meaning for email and consent by marking them mandatory and explaining the missing-field elicitation, but it does not clarify optional parameters like name, projet, telephone, or type_projet beyond what the schema already shows.

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 tool's action: 'prepare une demande de rappel' and identifies it as the 'PREMIERE etape' of a write flow. The returned action_id 'a confirmer par l'utilisateur' distinguishes it from confirmation and cancellation siblings.

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 description gives clear context: this is the first step, and the returned action_id still needs user confirmation. It implies the next step in the workflow but does not explicitly name confirmer_action or state when not to use this tool.

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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