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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 profiles matching a skills mix across internal resources and candidates, sorted by best fit. Ideal for pre-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
competencesYesCompétences recherchées en texte libre (ex: 'Java Spring AWS Kubernetes', '.NET Azure DevOps').
experience_minNoNiveau d'expérience minimum en texte libre (ex: '5 ans', 'senior'). Le modèle le mappera vers `experiences` via le dictionnaire.
dispo_avantNoDisponibilité requise au plus tard à cette date (YYYY-MM-DD). Si fourni, applique `period: 'available'` + `endDate`.
inclure_candidatsNo'oui' (défaut) pour inclure aussi les candidats actifs ; 'non' pour ne chercher que dans les ressources internes.
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).
Behavior4/5

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds important behavioral context: it returns a 'runbook texte' that the model must execute by calling other Boond tools. This goes beyond the annotations, clarifying the tool's role in a multi-step process.

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 concise, with two clear sentences in French that cover the tool's action, context, and output format. Every sentence serves a purpose, and the structure is front-loaded with the core function.

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

Completeness5/5

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

With no output schema, the description adequately explains the return value (a runbook text to be executed). It covers the tool's role in the workflow, sorting mechanism, and integration with other tools. For a 5-parameter tool with high schema coverage, this is complete and sufficient.

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, with each parameter already documented (e.g., competences, experience_min, etc.). The tool description does not add additional meaning beyond what the schema provides, so the baseline 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 searches for a profile matching a mix of skills, cross-referencing internal resources and candidates, and outputs results sorted by relevance. It distinguishes itself from sibling workflow tools by specifying its role as a pre-staffing/opportunity qualification step and its equivalence to a prompt, making its purpose unique.

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 provides explicit context for when to use the tool: 'en amont d'un staffing ou d'une opportunité non encore qualifiée'. It also explains it serves as an alternative for clients lacking proper MCP prompt handling. However, it does not specify when not to use it or list alternative tools, so a perfect score is not achieved.

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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