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fauguste

boondmanager-mcp-server

by fauguste

Recherche multi-source d'un profil par compétences

boond_workflow_recherche_profil_competences
Read-onlyIdempotent

Search for a profile matching a skill mix across internal resources and candidates, ranked by fit. Ideal before staffing or unqualified opportunities.

Instructions

Recherche un profil correspondant à un mix de compétences libres, en croisant ressources internes et candidats. Sortie classée par adéquation. Utile en amont d'un staffing ou d'une opportunité non encore qualifiée. Équivalent en outil du prompt MCP recherche_profil_competences (utile pour les clients qui ne gèrent pas correctement les prompts MCP, ex: claude.ai). Retourne un runbook texte que le modèle doit ensuite exécuter en appelant les outils Boond référencés.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
manager_idNoManager pour restreindre le scope ressources internes. Accepte soit l'ID numérique, soit « Prénom Nom » (le serveur résoudra automatiquement via `boond_resources_search`). Sinon scope ouvert (toute l'organisation accessible).
competencesYesCompétences recherchées en texte libre (ex: 'Java Spring AWS Kubernetes', '.NET Azure DevOps').
dispo_avantNoDisponibilité requise au plus tard à cette date (YYYY-MM-DD). Si fourni, applique `period: 'available'` + `endDate`.
experience_minNoNiveau d'expérience minimum en texte libre (ex: '5 ans', 'senior'). Le modèle le mappera vers `experiences` via le dictionnaire.
inclure_candidatsNo'oui' (défaut) pour inclure aussi les candidats actifs ; 'non' pour ne chercher que dans les ressources internes.
Install Server

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the read-only nature is clear. The description adds valuable behavioral context beyond annotations: it returns a runbook text that the model must execute by calling other Boond tools, and that output is sorted by fit ('Sortie classée par adéquation'). This is transparent about the indirection behavior.

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 compact and front-loaded. Each sentence contributes: function, output format, usage context, equivalence to a prompt, and behavioral note. It is slightly longer than necessary but remains efficient for the complexity of a workflow tool.

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?

Given there is no output schema, the description's explanation that the tool returns a runbook text is essential and provided. It also clarifies the multi-source nature and the intended usage phase. The description is complete enough for an agent to invoke the tool and anticipate the next steps, though it could elaborate on how the runbook is structured.

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 parameter semantics are fully documented in the schema. The description reinforces the meaning of 'competences' as free-text and mentions the cross-source behavior, but it does not add new parameter-specific details beyond what the schema already provides. Base score of 3 is appropriate.

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 function: 'Recherche un profil correspondant à un mix de compétences libres, en croisant ressources internes et candidats.' It specifies the verb (recherche), the resource (profil), and the scope (multi-source). It also distinguishes itself from direct search tools by noting it returns a runbook to execute, and defines its relationship to a named MCP prompt.

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 explicit usage context: 'Utile en amont d'un staffing ou d'une opportunité non encore qualifiée.' It also explains when this tool is preferable ('utile pour les clients qui ne gèrent pas correctement les prompts MCP'). However, it does not explicitly exclude alternatives like direct resource/candidate search tools, so it stops short of full when-not 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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