count_clientsGet total count of clients for the account
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | How many clients the account has — compare against the plan allowance. | |
| success | Yes | True when the call succeeded. A failure comes back as an error result instead. |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "$schema": "http://json-schema.org/draft-07/schema#",
+ "additionalProperties": false,
+ "properties": {
+ "data": {
+ "additionalProperties": {},
+ "description": "How many clients the account has — compare against the plan allowance.",
+ "type": "object"
+ },
+ "success": {
+ "description": "True when the call succeeded. A failure comes back as an error result instead.",
+ "type": "boolean"
+ }
+ },
+ "required": [
+ "success"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only and non-destructive behavior, so the description only needs to add beyond that. It adds the account-level scope and aggregate 'total count' nature, but does not address whether archived clients are included or how the count is computed. That is acceptable given the output schema and simple nature of the operation.
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 a single declarative sentence with no filler. It front-loads the action, resource, and scope, and every word contributes meaning.
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?
For a zero-parameter, read-only count operation with an output schema, the one-sentence description is complete enough for an agent to invoke it correctly. Return-value specifics are already covered by the output schema, and the annotations cover safety traits.
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 tool has zero parameters, so there is no parameter semantics for the description to add. The baseline for 0-parameter tools is 4, and the description is consistent with this by not implying any configurable inputs.
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 names a specific verb ('Get'), a specific resource ('clients'), and the scope ('for the account'). The phrase 'total count' clearly distinguishes it from list_clients by signaling an aggregate operation rather than a detailed listing.
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 implies account-level usage through 'for the account,' but it does not explicitly state when to choose this tool over alternatives like list_clients or count_unread_notifications. There is no exclusionary guidance, only an implicit selection condition.
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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