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Nodehour: GPU capacity sized from your run and quoted by providers

About Nodehour

describe_business
Read-onlyIdempotent

What Nodehour does (GPU capacity sized from your run and quoted by providers: Describe the training run or serving fleet. Nodehour sizes the cluster, takes one requirement to providers that can run it, and returns options side by side to choose from.), what happens to a request, what you receive, its scope, and the request fields with examples.

Tool call template

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": "describe_business"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds that the content covers process, scope, and request fields with examples, which is modest extra context about the payload. It does not say how long the content is, whether it is static documentation, or how to navigate it.

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

Conciseness3/5

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

It is short, but structured as one run-on sentence with a large nested parenthetical that interrupts the main clause. The leading 'What Nodehour does' is front-loaded, yet the rest is a comma-spliced list of topics that reads more like a table of contents than a purpose statement.

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 zero-parameter, read-only documentation tool with no output schema, the description is reasonably complete: it enumerates the topics the response covers (capabilities, request lifecycle, output, scope, field examples). Only the absence of explicit routing guidance against the transactional siblings keeps it from being fully complete.

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

Parameters4/5

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

The tool takes zero parameters, so the baseline of 4 applies; there is nothing for the description to disambiguate. The reference to 'request fields with examples' at least signals that field-level detail lives in the returned content rather than in the input schema.

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

Purpose3/5

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

The description frames the tool as an explainer of the Nodehour service (sizing, quoting, options) rather than stating a clear action like 'returns documentation about how Nodehour works'. The parenthetical 'Describe the training run or serving fleet...' describes the product's workflow, not this tool's operation, so an agent must infer that this tool returns explanatory text. It is distinguishable from the transactional siblings (submit_request, accept_offer) but only by inference.

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

Usage Guidelines2/5

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

There is no explicit statement of when to call this versus the many sibling tools, nor any guidance such as 'call before submit_request to learn the required fields'. The mention of 'the request fields with examples' hints at onboarding use, but the agent is left to infer the ordering and conditions itself.

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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