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boondmanager-mcp-server

by silamir
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TypeScript
Hybrid

Demandes d'absence à valider

boond_workflow_absences_a_valider
Read-onlyIdempotent

Lists pending absence requests for a team, cross-checks them with existing absences, and prepares a motivated validation or refusal decision for each.

Instructions

Liste les demandes d'absence en attente de validation sur une équipe, les recoupe avec les absences déjà posées sur la période, et prépare la décision (validation ou refus motivé) pour chacune.

Quand : pour dérouler ce scénario multi-étapes sans avoir à retrouver soi-même le bon enchaînement d'outils et les bons noms de filtres. Plutôt que : le prompt MCP absences_a_valider si le client l'expose — contenu identique, sans consommer un appel d'outil. Cette variante existe pour les clients qui traitent mal prompts/get (claude.ai notamment).

  • N'appelle aucune API BoondManager et ne lit aucune donnée : la réponse est générée côté serveur MCP.

Returns : un runbook en texte — la liste ordonnée des appels Boond à effectuer, avec les filtres exacts. C'est ensuite au modèle de les exécuter ; rien n'est fait par cet appel.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
moisNoMois des absences : `YYYY-MM`, « ce mois », « mois dernier », « avril 2026 »… Défaut : le mois en cours.
manager_idNoManager pour restreindre à son équipe (les demandes de ses N-1). Accepte soit l'ID numérique, soit « Prénom Nom » (le serveur résoudra automatiquement via `boond_resources_search`). Si absent, scope = mon équipe via `perimeterDynamic: ['managers']`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.17.0

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, but the description adds critical behavior beyond them: 'N'appelle aucune API BoondManager et ne lit aucune donnée' and 'rien n'est fait par cet appel'. This makes clear the tool is a server-side runbook generator, not an actual data reader or validator.

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 description is well-structured with Quand, Plutôt que, and Returns sections, and it front-loads the essential no-API behavior. Some redundancy exists between 'N'appelle aucune API...' and 'rien n'est fait par cet appel', and the text is moderately long, but each section earns its place.

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 two-parameter, no-API, runbook-returning tool, the description is nearly complete: it explains the output type, that the model must execute the generated calls, and which alternative to prefer. With no output schema, it could be slightly more explicit about the runbook's format and edge cases, but it covers all essential invocation information.

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?

The input schema has 100% description coverage and already thoroughly documents both `mois` and `manager_id`, including formats, automatic resolution via `boond_resources_search`, and the default 'mon équipe' scope. The description itself adds no additional parameter-level semantics, so the baseline score of 3 applies.

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?

States a specific verb and resource: lists absence requests pending validation for a team, cross-references them with already-recorded absences, and prepares a validation or motivated refusal decision. It also clearly distinguishes itself from the MCP prompt variant and from data-reading tools by stating it returns a runbook and makes no API call.

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

Usage Guidelines5/5

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

The 'Quand' section explicitly says to use it for this multi-step scenario without having to discover the tool chain and filter names manually. The 'Plutôt que' section names the MCP prompt `absences_a_valider` as the preferred alternative when supported, giving explicit routing guidance.

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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