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buy

Buyer: start a purchase; returns pay_url for your principal. First time? Try listing_id "ls_sandbox" with test: true: the whole flow without money.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
viaNoagent_id of the agent that sold you this (it earns the reseller share the seller set; you pay the listed price, nothing more)
testNowith listing_id "ls_sandbox": the whole flow without money (delivery and a real signed receipt, nothing stored or charged)
inputNowhat the seller needs to deliver
dry_runNocheck everything (seller ready, budget, price, contract) without creating an order
pay_withNodefault card (pay on delivery). Crypto goes straight to the seller's wallet before delivery, if the seller accepts it (see accepts in get_listing).
listing_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses one important behavior (returns pay_url, and test/sandbox mode moves the whole flow without money), but is silent on permissions, what happens to the listing/order after payment, reversibility, or whether the buyer is charged immediately. Adequate but incomplete for a payment-initiating 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?

Two compact sentences, front-loaded with the core action and its return value, then the onboarding hint. Nothing is padded, though the sandbox aside is somewhat tangential to the primary definition.

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 6-parameter, no-annotation, no-output-schema mutation tool, the description covers the primary return (pay_url) and the trial path but omits what follows purchase (payment confirmation, receipt/order retrieval) and the relationship to sibling tools. Enough to call it, not enough to call it correctly end-to-end.

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 83%, so the schema already documents via, test, dry_run, pay_with, and input well. The description adds little parameter meaning beyond reiterating listing_id "ls_sandbox" + test: true, leaving required-param semantics to the schema. Baseline 3 applies when the schema does the heavy lifting.

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

Purpose4/5

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

States a specific verb+resource ("start a purchase") and names the key output ("returns pay_url for your principal"), so an agent knows this initiates an order rather than inspecting one. It does not explicitly distinguish itself from siblings like quote, get_order, or confirm_crypto_payment, but the action is unambiguous.

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 a useful first-time hint (try listing_id "ls_sandbox" with test: true) which tells the agent when to use a safe trial mode. However, it gives no guidance on when to buy vs. quote, when to use dry_run first, or the required sequence with confirm_crypto_payment – usage is implied rather than directed.

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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