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Lium GPU Cloud: live GPU prices and rent links

by io.github.Datura-ai
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Estimate Lium provider earnings

estimate_provider_earnings
Read-only

Estimate what a provider earns per month on Lium by listing GPUs of a model, as the rewards calculator does: rental income (95% of the renter price) and rented extra at the last 30 days' utilisation, plus idle pay at the validator's rate for every unrented hour; with what those GPUs actually earned and the middle-half range of that potential across providers. Use when someone asks what their GPUs could earn on Lium; for renting GPUs use search_gpus. An estimate, not a guarantee.

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": "estimate_provider_earnings"
  }
}

Input Schema

NameRequiredDescriptionDefault
gpuYesGPU model, e.g. H100, B200, RTX 4090 (case and spacing ignored)
countNoHow many GPUs of that model (default 1)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, and the description is fully consistent with them. Beyond that it discloses the calculation basis — 95% of renter price, last 30 days' utilisation, idle pay at the validator's rate for unrented hours — which the agent cannot infer from the schema. It stops short of describing output shape or any latency/rate characteristics, but the methodology disclosure is substantial.

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

Conciseness4/5

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

The purpose is front-loaded in the opening clause and every clause contributes information (income formula, utilisation window, idle pay, cross-provider range, usage trigger, caveat). The middle section is a dense run-on that packs several concepts into one sentence, costing some readability, but there is no filler.

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

Completeness5/5

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

For a two-parameter read-only estimator with no output schema, the description covers what is computed, over what window, what the result contains (rental income, idle pay, actual earnings, middle-half range), and how confident the agent should be. Nothing needed to call it correctly or interpret the response is missing.

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 description coverage is 100%, with both 'gpu' and 'count' fully documented (including case/spacing handling and the 1–64 bound), so the baseline is 3. The description only implies the inputs via 'listing GPUs of a model' and adds no format, validation, or default detail beyond what the schema already carries.

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

Purpose5/5

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

States a specific verb and resource ('Estimate what a provider earns per month on Lium') and immediately scopes it to 'listing GPUs of a model', so an agent knows it takes a GPU model and returns a monthly earnings estimate. It also distinguishes itself from the renting path by naming search_gpus as the sibling for that instead.

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

Usage Guidelines5/5

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

Gives an explicit trigger ('Use when someone asks what their GPUs could earn on Lium') and an explicit alternative ('for renting GPUs use search_gpus'), which is exactly the when-this / when-not-this split an agent needs. The closing caveat 'An estimate, not a guarantee' further frames how to present the result.

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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