Skip to main content
Glama

Model conditions report (paid: 0.01 RLUSD or 0.01 USDC on Base via x402)

get_model_report
Read-only

Paid: 0.01 RLUSD per call via x402 on XRPL mainnet (xrpl:0), or 0.01 USDC on Base (eip155:8453). Conditions report for one AI model as declared by public sources: prices, limits, modalities, listing events and vendor status. Not a ranking and makes no statement about model performance. Find ids with the free list_models tool. Without payment this returns isError with the x402 PaymentRequired object (fresh invoiceId); retry with the signed payload in _meta["x402/payment"] or the payment_signature argument. Unpaid calls cost nothing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesModel id from list_models, e.g. openai/gpt-4o
payment_signatureNoOptional. Base64 x402 PAYMENT-SIGNATURE value (signed RLUSD or USDC PaymentPayload) for hosts that cannot set _meta["x402/payment"]. Omit on the first call to receive the payment requirements.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / payment_signature / description
      Previous value: -"Optional. Base64 x402 PAYMENT-SIGNATURE value (signed RLUSD PaymentPayload) for hosts that cannot set _meta[\"x402/payment\"]. Omit on the first call to receive the payment requirements."New value: +"Optional. Base64 x402 PAYMENT-SIGNATURE value (signed RLUSD or USDC PaymentPayload) for hosts that cannot set _meta[\"x402/payment\"]. Omit on the first call to receive the payment requirements."
  2. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Despite annotations carrying readOnly/openWorld, the description adds substantial context annotations cannot express: exact cost per chain, the x402 payment flow, that an unpaid call returns isError with a PaymentRequired object and a fresh invoiceId, the retry path via _meta["x402/payment"] or payment_signature, and that failed unpaid calls are free. This covers non-idempotent behavior (fresh invoiceId) and error semantics richly.

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?

Every sentence carries information and nothing is redundant, but the payment mechanics are front-loaded ahead of the actual purpose, and the paragraph is dense enough that the core 'what it returns' arrives late. Slightly better ordering would put the purpose first.

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?

With no output schema, the description must explain what comes back, and it does: the report fields are enumerated, the error/payment-required behavior is documented, and the retry contract is spelled out. Nothing an agent needs to invoke it correctly is missing.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning beyond the schema: it explains the role of payment_signature as a workaround for hosts that cannot set _meta["x402/payment"], a distinction the schema does not fully convey. It does not add syntax detail for id beyond pointing to list_models.

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?

Names a specific verb+resource ('conditions report for one AI model') and enumerates exactly what it contains: prices, limits, modalities, listing events, vendor status. It also explicitly carves out what it is not ('not a ranking and makes no statement about model performance'), which separates it from ranking/decision siblings like decide_cheapest_model.

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

Usage Guidelines4/5

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

Tells the agent how to obtain the required id ('find ids with the free list_models tool') and what to do without payment, so the workflow is clear. It does not, however, explicitly say when to prefer this over get_current_conditions or other conditions siblings, leaving some alternative selection to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources