Each engine this API key can call: whether it is down now, and the share of its newest requests that answered, everyone's and this organization's own (100 with none).
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "engines"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish that this is a read-only, closed-world operation. The description adds useful behavioral context beyond that: it reports whether an engine is down now and gives both global and organization-specific success shares, including the '100 with none' default. It does not discuss rate limits or time windows, so it is not exhaustive.
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 definition is a single compact sentence with the primary resource front-loaded. The parenthetical '(100 with none)' is somewhat cryptic and the sentence is grammatically dense, but there is little wasted wording.
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 listing tool with no output schema, the description adequately sketches the returned data. However, it leaves ambiguities about what 'newest requests' means, the aggregation window, and the exact shape of the response, which an agent would need in order to interpret results confidently.
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 input parameters, so the baseline is 4. The description does not need to explain parameter meaning, and it appropriately focuses on the result content instead.
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 identifies the resource as 'each engine this API key can call' and states that it reports current down status and request-success shares. That is specific enough to distinguish this listing tool from the sibling tools, which are individual engine endpoints, though it never explicitly contrasts itself with them.
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?
Usage is implied: an agent would call this to discover available engines and check health/success rates. There is no explicit guidance on when to use this versus calling a sibling like google or openai directly, nor any stated exclusions or prerequisites beyond the API-key scope.
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.