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Cheapest cloud price for a GPU

cheapest_gpu
Read-onlyIdempotent

Cheapest public on-demand rental price for one GPU model (e.g. H100, A100, L40S, RTX 4090), with provider, source URL and comparison page.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "gpu": "<gpu>"
    },
    "name": "cheapest_gpu"
  }
}

Input Schema

NameRequiredDescriptionDefault
gpuYesGPU model, e.g. H100, H200, A100, L40S

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's main added value is scoping the data to 'public on-demand rental' prices and disclosing the returned fields (provider, source URL, comparison page), which matters because there is no output schema. It does not disclose currency, unit (per hour vs. per month), or how ties/staleness are handled.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One sentence, front-loaded with the resource and the key scope qualifier, followed by the return contents. Nothing is repeated from the title or schema and there is no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter, read-only lookup with no output schema, the definition covers what it returns and which price type it uses, which is nearly enough. The remaining gap is the price unit and currency, which an agent needs to interpret the result correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the single parameter is fully documented, so the baseline of 3 applies. The description adds only a slightly different example set (RTX 4090) and reinforces the singular 'one GPU model' constraint, without stating accepted formats, case sensitivity, or alias handling (e.g. 'A100 80GB').

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource and scope: the single cheapest public on-demand price for one named GPU model, returning provider, source URL and comparison page. It is clearly narrower than a bulk price feed, but it never names the sibling tools (get_prices, list_gpus) so the agent must infer the distinction from scope alone.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied: the phrase 'for one GPU model' signals a single-model, minimum-price lookup rather than a listing. There is no explicit when-to-use/when-not-use statement and no routing to get_prices or list_gpus for multi-GPU or full-catalog needs.

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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