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bazaar_pay_and_call

Pay a Loyal Spark x402 URL on api.loyalspark.online with the merchant agent's CDP MPC wallet (EIP-3009 exact scheme, Base USDC). Other hosts are refused before any signature. Requires scope 'mint' and an active CDP wallet. max_usdc default 0.25, hard limit 10.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull https:// URL of the x402 resource
bodyNoOptional JSON request body for non-GET methods
methodNoHTTP method (default GET)
headersNoExtra request headers (Accept/Content-Type auto-set)
max_usdcNoSpend cap for THIS call in USDC (default 0.25, must be ≤ 10)
allowed_schemesNox402 schemes to accept (default ['exact'])
allowed_networksNoNetworks to accept (default ['base'])

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
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: it discloses the payment scheme (EIP-3009 exact), settlement network/asset (Base USDC), that host refusals occur before any signature, the required scope and wallet state, and the spend cap defaults/limits. It stops short of describing outcome semantics such as what happens on payment failure or response/return behavior, so it is strong but not exhaustive.

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?

It is compact and front-loaded, leading with the core action and host scope before prerequisites and caps. The dense packing of scheme/network/wallet terms is efficient, though the payment jargon compresses several distinct constraints into one long sentence.

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

Completeness3/5

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

For a payment tool with 7 parameters and no output schema, the description covers host scoping, scheme, authorization, and spend limits well. It omits what the call returns (the proxied HTTP response, payment receipt, or failure mode), which is important context for a tool whose return contract is otherwise undocumented.

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 the schema already documents all seven parameters including max_usdc semantics. The description only restates the max_usdc default (0.25) and hard limit (10), which duplicates the schema rather than adding new meaning; baseline 3 is appropriate.

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 (Pay) and resource (Loyal Spark x402 URL) along with the mechanism (CDP MPC wallet, EIP-3009 exact scheme, Base USDC). This clearly distinguishes it from siblings like bazaar_probe_x402 (probe) and bazaar_discover_resources (discover), so an agent can route correctly.

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?

The description gives meaningful preconditions ('Requires scope mint and an active CDP wallet') and a host restriction ('Other hosts are refused before any signature'), which is a form of when-not guidance. However, it never names the natural alternative (e.g., bazaar_probe_x402) or explains when to pay versus probe/discover, leaving the tool-selection decision implicit.

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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