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Glama

quote_x402

Ask what an x402 endpoint charges without paying: fetches the URL, parses the 402 requirements, says which option this wallet would pay (chain, asset, amount, recipient), whether the per-payment cap, the spend policy and the rolling…

Instructions

Ask what an x402 endpoint charges without paying: fetches the URL, parses the 402 requirements, says which option this wallet would pay (chain, asset, amount, recipient), whether the per-payment cap, the spend policy and the rolling budgets would allow it, and nothing is signed. Call it before pay_x402 when the price is unknown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL to quote
bodyNoOptional request body, as for pay_x402
methodNoHTTP method the real request would useGET
headersNoOptional JSON string of request headers, as for pay_x402
prefer_chainNoPreferred chain ID when several are offered

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.14.2

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: 'nothing is signed' is a critical safety disclosure given siblings like sign_transaction and pay_x402, and it reveals the tool evaluates the per-payment cap, spend policy and rolling budgets rather than just reading a price. It stops short of stating auth requirements, rate limits, or failure behavior when the endpoint is not x402, leaving some gaps for a no-annotation tool.

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?

A single long sentence, but it is front-loaded with the core action ('Ask what an x402 endpoint charges without paying') before enumerating what gets returned. Dense and mostly waste-free, though the list-heavy clause makes it slightly run-on.

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 or annotations, the description compensates by describing what the tool returns (chain, asset, amount, recipient, and policy/budget allowance verdicts) and confirming no signature is produced. That is sufficient for an agent to call and interpret it 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 description coverage is 100%, so all five parameters (url, body, method, headers, prefer_chain) are already documented in the schema. The description adds only indirect context by mentioning chain/asset/amount/recipient as outputs of a preferred-option selection; it does not explain parameter syntax or interactions beyond the schema.

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?

The description states a concrete verb+resource (fetch a URL and parse its 402 requirements without paying) and explicitly contrasts itself with pay_x402, which performs the actual payment. An agent can distinguish quote_x402 from its payment sibling without opening either schema.

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?

It gives an explicit trigger: 'Call it before pay_x402 when the price is unknown.' The alternative and the condition that selects it are both named, leaving nothing to inference.

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