Cartographie des compétences d'un périmètre

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds valuable behavioral context beyond annotations: the tool returns a text runbook that the model must subsequently execute via referenced Boond tools, and the perimeter can be auto-resolved by agency/manager name. 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three focused, front-loaded sentences: core function, client context, and output behavior. Each sentence earns its place. The second sentence about the MCP prompt equivalence is slightly niche but relevant for adoption decisions, so the structure remains efficient without waste.

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

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 ('runbook texte') and its content (top/rare/missing skills). It covers the perimeter variants, the execution pattern, and the client context. Minor gaps: no detail on runbook format, which Boond tools are referenced, or edge cases like empty perimeters, but this is acceptable for a composite workflow tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with rich, self-sufficient parameter descriptions (defaults, alternatives, auto-resolution via `boond_agencies_search`/`boond_resources_search`, and default scope behavior). The description's mention of 'équipe, agence' and 'top compétences' subtly reinforces the parameters' roles, but it adds no essential information beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Produit une cartographie') and a clear resource (compétences techniques d'un périmètre), and enumerates the concrete outputs (top compétences, compétences rares/risque bus-factor, compétences manquantes). It distinguishes itself from sibling workflows like `boond_workflow_recherche_profil_competences` by framing this as a perimeter-level mapping rather than a profile search.

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

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

The description gives contextual usage signals: it is the tool equivalent of the MCP prompt `cartographie_competences`, useful for clients (e.g., claude.ai) that don't handle MCP prompts well. It also explains that the returned runbook must be executed by the model. However, it does not explicitly state when to prefer this over sibling workflow tools, nor does it mention any exclusions or alternative tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.