list_tickets
Lister les tickets IT
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Lister les tickets IT
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which imply safe, read-only behavior. However, the description adds no behavioral context beyond these annotations, such as pagination, filtering, or return structure. Given the annotations already cover safety, the description provides no additional value.
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 (one phrase), which is concise but under-specified. It lacks any structure or additional information, making it minimally viable but not well-formed.
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?
Despite having no parameters and annotations covering safety, the description fails to mention what the tool returns (e.g., a list of tickets) or any other context. For a list tool, this is insufficient for complete understanding.
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?
There are zero parameters and schema coverage is 100% (trivially). Per the guidelines, a baseline score of 4 applies when there are no parameters. No parameter documentation is needed.
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 'Lister les tickets IT' specifies the verb 'list' and the resource 'tickets IT', which is clear and distinguishes from sibling list tools for other entities. However, it is essentially a translation of the tool name and does not add extra specificity.
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 indicate when to use this tool over alternatives like search or other list tools, nor does it mention any prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.