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How payments work

payment_info
Read-only

No balances, no deposits: buyers pay sellers USDC on Base from their own wallet and submit the transaction hash; the platform verifies it on-chain. Returns network, USDC contract, confirmations, how to pay (gas-free first: sign typed data, a public facilitator broadcasts it), funding guide, wallet requirements. Test keys use Base Sepolia; sandbox_faucet gives you the testnet USDC.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
envNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses substantial behavioral detail: no balances or deposits are involved, buyers pay from their own wallet, the platform verifies on-chain, and the gas-free payment path uses signed typed data broadcast by a public facilitator. It also clearly distinguishes testnet behavior and points to sandbox_faucet, giving agents an accurate model of what the tool does and does not do.

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

Conciseness5/5

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

Three dense sentences cover the payment mechanism, the returned fields, the gas-free flow, and testnet guidance without wasted words. The most important conceptual framing ('No balances, no deposits') is front-loaded, making the tool easier to understand immediately.

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 single-optional-parameter info tool with a readOnly annotation, the description is remarkably complete. It tells the agent what the tool returns, what payment model it describes, how the gas-free payment path works, and how testnet differs from live. An agent can confidently decide to call this tool and interpret its output.

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?

The schema provides no descriptions for the env parameter, so the description must compensate. It does so partially by noting that test keys use Base Sepolia and that sandbox_faucet provides testnet USDC, which implies the env parameter toggles test versus live environment. However, it never explicitly maps env values to their effects, leaving some room for misinterpretation.

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 clearly states the tool's role: explaining how payments work, including the USDC-on-Base flow, required inputs from the buyer, and what information the tool returns. It distinguishes this informational tool from action-oriented sibling tools like pay_job and sandbox_faucet by describing it as an explainer rather than an executor.

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?

The description makes the informational context clear: it returns how to pay, funding guidance, and wallet requirements, implying it should be consulted before payment actions. It also mentions sandbox_faucet for obtaining testnet USDC, which gives a useful pointer. However, it does not explicitly exclude alternatives or state when this should not be used.

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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