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Get payment result

get_payment_result

Read the result of a paid call, by its paymentId. Use it when pay_service answered {"status":"pending"} (the service was still working when the Router stopped waiting — the payment is made and the call keeps running), or to recover a result whose response you lost. Reading costs nothing and charges nothing. state: "Pending" — still running, call again in a few seconds. state: "Ready" — status is the service's HTTP status and body its response (bodyEncoding says whether it is parsed JSON, text, or base64). state: "Failed" — the call ended without a response; failureReason says why. {"status":"not_available"} — nothing to return: results are kept for 24 hours for the account that paid, and only then. Do NOT call pay_service again to get a pending result: that returns the same pending answer. Requires your Nevermined API key on the Authorization header.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paymentIdYesThe `paymentId` a pay_service result returned.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations to lean on, the description carries the full burden and does so: it discloses that reading is free, that results are retained 24 hours only for the paying account, and requires the Nevermined API key on the Authorization header. The state machine (Pending/Ready/Failed/not_available) and their meanings are spelled out, which is exactly the behavioral context an agent needs.

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?

Front-loads the purpose and the primary use case, then answers the state semantics in compact labeled form ('state: X' — meaning). Every sentence carries information, though the paragraph is denser than strictly necessary.

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?

No output schema exists, and the description fully compensates by explaining the returned fields (`state`, `status`, `body`, `bodyEncoding`, `failureReason`) and the failure/empty cases. Nothing an agent needs to interpret a call is missing.

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?

Only a single parameter with 100% schema coverage, so the schema already documents `paymentId` as a UUID from a pay_service result. The description adds only the minor nuance that the value originates from a pay_service result, so 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 and resource ('Read the result of a paid call') scoped by `paymentId`, and clearly distinguishes itself from the sibling `pay_service` it complements. An agent can tell exactly what this returns without opening the 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?

Explicitly names the two triggering conditions ('when pay_service answered pending' and 'to recover a result whose response you lost') and adds an explicit when-not ('Do NOT call pay_service again to get a pending result'). This is textbook routing guidance.

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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