Cheapest GPU price across all venues
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": "gpu_cheapest"
}
}| 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?
No annotations are provided, so the description carries the full disclosure burden, yet it says nothing about read-only behavior, whether prices are live or cached, currency/units, or whether fees are included. For a market-data lookup these are exactly the traits an agent needs before trusting the number.
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?
One short front-loaded fragment with no filler or repetition. It is a noun phrase rather than a sentence, so it is terse to the point of being skeletal, but nothing in it is wasted.
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?
The tool is simple, but with no annotations and no output schema there is no structured source describing the return value, and the description does not fill that gap. An agent cannot tell whether it gets a bare number, a venue plus price, or a ranked list, nor how fresh the data is.
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 takes zero parameters, so there is no parameter semantics to document; the baseline of 4 applies. The description correctly implies no filtering or venue selection is possible, which matches the empty schema.
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 phrase 'Cheapest GPU price across all venues' names a specific resource (GPU price) and a specific aggregation/scope (cheapest, across all venues), which lets an agent distinguish it from gpu_quote or list_compute_offer. It lacks an explicit verb and never names those siblings, so differentiation is inferred rather than stated.
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?
There is no statement of when to call this versus gpu_quote, exchange_book, or list_compute_offer. The 'across all venues' wording implies a global aggregation use case, but no exclusions, prerequisites, or alternative-selection guidance are given.
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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