sweipe_ai_pingConfirms Sweipe AI licence acceptance and returns the credit balance with monthly credits, used, left, and reset date.
Round trip to the Sweipe AI service: confirms the licence is accepted and returns the credit balance (included monthly credits, used, left, reset date).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that it is a round-trip network call and what it returns (licence acceptance, credit balance details). However, it does not mention potential side effects (though likely read-only), error behavior, or whether it incurs costs or rate limits. It adds some behavioral context beyond the schema, which is empty.
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?
A single, well-structured sentence that leads with the core action and immediately specifies the return value. No wasted words; it is front-loaded and efficient.
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 tool with no output schema, the description covers the essential return information (credit balance components). It does not mention error cases or whether the licence acceptance is a precondition for other calls, but for a simple ping tool it is nearly complete. A slight gap is the lack of any note on expected response format or failure modes, but it is adequate for its simplicity.
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 the schema provides no parameter info. The baseline for 0 params is 4. The description correctly adds no parameter details since none exist, and it does not mislead. The credit balance details in the description give some context about what the response will contain, but that is not parameter semantics.
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 clearly states a specific verb ('Round trip'), the resource ('Sweipe AI service'), and the outcome (confirms licence, returns credit balance). It distinguishes itself from siblings like sweipe_ai_get_plan (plan details) and sweipe_status (general status) by specifying its exact scope.
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 guidance on when to use this tool versus alternatives. It does not state that it is a lightweight health check or a prerequisite for other sweipe operations. The agent is left to infer its role from the purpose, with no explicit exclusions or preferred conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.