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get_payment_link

Get a link a person can open to buy more delivery attempts for this project: 50,000 attempts for $5.00. Attempts left over carry over, and the whole balance stays valid for 12 months from the purchase. Returns payment_url and/or mpp_url, depending on what is available. payment_url is a page where a person pays by card through Stripe (works for 24 hours; pass it to your user). mpp_url: if you can pay with MPP (Machine Payments Protocol, e.g. npx @stripe/link-cli mpp pay <mpp_url> -X POST), POST it, pay the 402 challenge, and the attempts are added at once (works for 7 days). Check the result with get_project.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

No annotations are supplied, yet the description fully explains the terms of operation: price and quantity, that leftover attempts carry over, a 12-month validity window, the 24-hour lifetime of payment_url vs the 7-day lifetime of mpp_url, and the fact that MPP payment credits attempts immediately while card payment requires the user to act. It also names the sibling (get_project) that confirms the result, which is the key post-call behavior 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.

Conciseness5/5

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

Purpose and price are front-loaded in the first clause, followed by the terms, then a per-return-value breakdown with lifetimes and the action to take for each. Though it is longer than most, every sentence conveys decision-relevant information, including the concrete MPP command example, and there is no filler.

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 zero-parameter tool with no output schema, the description compensates by documenting both possible return fields (payment_url and mpp_url), their lifetimes, and the follow-up check via get_project. An agent can pick the right payment path and know how to close the loop without inspecting anything else.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so parameter semantics carry no burden and the baseline of 4 applies. The description instead invests its detail in the return values, which is the useful place for a no-arg tool.

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 opens with a specific verb (get) and resource (a link) and states exactly what the link buys: 50,000 delivery attempts for $5.00 for this project. This is clearly distinct from every sibling tool (get_project, create_project, etc.) with no overlap in intent.

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?

It gives concrete usage instructions: pass payment_url to your user, POST to mpp_url and pay the 402 challenge when MPP is available, and verify the outcome with get_project. What's missing is an explicit trigger condition (e.g. 'use when attempts run low or after an insufficient-attempts error') and any when-not-to-use guidance, so the agent still has to infer when to call it.

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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