dashboard_kpis
KPIs du dashboard principal
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
KPIs du dashboard principal
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds domain context ('KPIs du dashboard principal') but does not elaborate on behavioral traits beyond what annotations provide.
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 concise: one short sentence that contains all necessary information. No wasted words.
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?
While the description is adequate for a simple tool with no parameters, it could be more informative by specifying what KPIs are returned or the format. Without an output schema, some detail is missing.
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?
No parameters exist, so baseline score is 4. The description does not need to explain parameters because schema coverage is 100% and there are none.
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 'KPIs du dashboard principal' clearly states it returns KPIs for the main dashboard. It distinguishes from sibling tools like 'dashboard_alerts', which likely returns alerts rather than KPIs.
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 explicit guidance on when to use this tool versus alternatives. However, the tool has no parameters and a self-evident purpose, so minimal guidance is needed.
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.