create_employee
Créer un employé
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Créer un employé
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are all false, offering no safety or behavioral hints. The description does not disclose any behavioral traits (e.g., required permissions, side effects, or return behavior). With no annotations to lean on, the description should carry the burden but fails to do so.
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?
The description is extremely short (two words in French), but it is underspecified rather than concise. It lacks critical information and does not earn its place as it provides no value beyond the name.
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?
Given the absence of input schema parameters, output schema, and annotations, the description is critically incomplete. It does not explain how to create an employee, what happens upon success, or any preconditions. The tool is unusable based on this definition alone.
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?
The input schema has no parameters (empty object) and schema description coverage is trivially 100%. Baseline for parameter semantics is 3 when coverage is high, but the description adds no extra meaning about parameters (e.g., that none are needed or that the schema is likely incomplete). It neither helps nor harms, hence a baseline score.
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 'Créer un employé' is French for 'Create an employee', which is essentially a translation of the tool name. While it identifies the resource, it adds no additional context and is essentially a tautology (repeating the name in another language). Among sibling 'create_*' tools, it distinguishes by resource but provides no scope or detail.
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?
No usage guidance is provided. The description does not specify when to use this tool versus alternatives like create_client or create_invoice, nor does it mention prerequisites or context. The agent receives no help in deciding which tool to invoke.
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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Most tools target distinct resources and actions (e.g., create_client vs. list_clients). However, generic tools like eyeot_call overlap with many specific tools, and there's potential confusion between convert_opportunity_to_quote, create_quote, and accept_quote, though descriptions help distinguish them.
The majority follow verb_noun pattern (create_client, list_invoices), but there are outliers like eyeot_call, eyeot_help, stock_dashboard, dashboard_kpis, whoami, and search. The mix of French and English is consistent but slight inconsistency in structure.
33 tools cover multiple ERP modules (CRM, HR, inventory, sales, IT). While on the higher end, each module has necessary operations. The presence of generic eyeot_call suggests the tool surface could be larger, but the count is still reasonable for the scope.
Only clients have update and no deletes exist. Many resources (products, employees, orders, quotes, invoices, opportunities, tickets) lack update/delete operations. This creates dead ends for agents that need to modify or remove data.