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Fiche publique d’un avocat / Lawyer public profile

fiche_avocat
Read-onlyIdempotent

Fiche publique complète d’un avocat à partir de son identifiant ou de l’URL de sa fiche dikoo.fr : nom, barreau, ville, spécialités, langues, modes de consultation, tarif de consultation affiché (avocats inscrits), prochaine disponibilité, lien de rendez-vous. Jamais d’email ni de téléphone. Full public profile of a lawyer from an id or dikoo.fr URL: name, bar, city, practice areas, languages, consultation modes, displayed fee (registered lawyers), next availability, appointment link. Never email or phone. DIKOO ne fournit pas de conseil juridique / DIKOO does not provide legal advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
avocatYesIdentifiant public (champ « id » d’un résultat) ou URL dikoo.fr de la fiche. Public id or dikoo.fr profile URL.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Read-only, idempotent, non-destructive behavior is declared in annotations, so the description needn't restate it. It does add valuable disclosure beyond annotations: the privacy guarantee ('Jamais d'email ni de téléphone' / 'Never email or phone') and that fees are only shown for registered lawyers, which tells the agent what data will be absent. It could go further on error behavior for an unknown id, but the explicit privacy constraint is meaningful.

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?

Dense but zero-waste: each clause enumerates a returned field or a constraint. The bilingual duplication and the legal disclaimer are front-loaded and purposeful. No filler sentences.

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 1-param read-only lookup with full schema coverage and no output schema, the description covers what the tool does, what it returns, and the key data-privacy boundary. It is nearly complete; only error/unknown-id behavior and pagination are unaddressed, which are minor for this tool shape.

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% and the parameter's description already explains 'Public id or dikoo.fr profile URL'. The description repeats this ('à partir de son identifiant ou de l'URL de sa fiche dikoo.fr') but adds no format details, no exclusions, no examples. Baseline 3 for full schema coverage.

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?

Names a specific resource (fiche publique d'un avocat) and specifies the lookup key (identifier or dikoo.fr URL). It enumerates the returned fields, which sharply distinguishes it from siblings like rechercher_avocats and creneaux_disponibles.

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

Usage Guidelines3/5

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

The description implies it is for fetching one profile by id or URL, and the enumeration of fields implies 'use when you already have an id', but it never states when NOT to use it or points to alternatives (e.g. rechercher_avocats for discovery, verifier_avocat for verification). Usage is inferable but not explicit.

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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