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get_ai_tokens_pay_link

Read-only

Get a real, payable Machine Payment Protocol (MPP) URL to top up AI Tokens ($0.10/token) — for use with an MPP-native payment agent (e.g. Stripe's link-cli), NOT with buy_ai_tokens's own payment flow (that tool's challenge cannot be paid by an external MPP agent). Use this ONLY when an MPP-native agent's tools (e.g. link-cli's mpp_pay) are available in this session.

PAYMENT PRIORITY: this is priority 2 for AI Tokens — reach for it only after buy_ai_tokens's own in-band payment flow (priority 1) isn't viable (no payment_token available from your own platform), and only when link-cli is present. Always hand over the exact server-computed pay_url/price returned here — never estimate or recompute the amount yourself. There is no checkout-link fallback for AI Tokens.

Returns a pay_url that a real HTTP 402 challenge is served from — hand it directly to the MPP agent's pay tool (e.g. mpp_pay) rather than fetching or decoding it yourself.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
token_countYesNumber of AI Tokens to purchase (5-100000; 5 is the $0.50 minimum).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
priceNo
pay_urlYesReal MPP-payable URL — hand this to an MPP agent, do not fetch it yourself.
successYes
currencyNo
expires_atNo
token_countYes

TDQS

A4.7/5.0
Behavior4/5

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

Annotations include readOnlyHint=true, which is consistent with the description's emphasis on not fetching or decoding the URL yourself. The description adds behavioral context: the URL is served from a real HTTP 402 challenge, and it must be handed directly to the MPP agent's pay tool. It also clarifies that the tool's own payment flow cannot be paid by an external MPP agent, which is important behavioral disclosure beyond the annotations.

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?

The description is well-structured with clear sections: purpose, usage priority, and return behavior. It is concise but packed with essential information, using bold for key terms and bullet-like structure. Every sentence adds value, and it is front-loaded with the core purpose.

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?

Given the tool's complexity (interaction with external MPP agents, priority ordering, and no fallback), the description is complete. It covers when to use, how to use, what to expect, and what not to do. The output schema exists, so return values are not needed in the description. The description fully compensates for the lack of annotations beyond readOnlyHint.

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 schema already provides 100% coverage for the single parameter token_count, including a description with range and minimum. The description adds context about the price ($0.10/token) and the minimum purchase, which reinforces the parameter's meaning. Since schema coverage is high, the baseline is 3, and the description adds a bit more value, so a 4 is justified.

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 purpose: to get a real, payable MPP URL for topping up AI Tokens. It specifies the resource (AI Tokens), the action (get a pay link), and distinguishes it from the sibling tool buy_ai_tokens by noting it is for use with an MPP-native payment agent, not buy_ai_tokens's own flow.

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?

The description provides explicit when-to-use guidance: use only when an MPP-native agent's tools (e.g., link-cli's mpp_pay) are available, and only after buy_ai_tokens's in-band payment flow isn't viable. It also states there is no checkout-link fallback, and instructs to hand over the exact server-computed pay_url/price, never estimate. This is exemplary usage 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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TDQS

A4.1/5.0
Disambiguation2/5

Several tools serve the same resource+action through different payment channels (e.g., register_domain, register_domain_spt, get_domain_register_pay_link; purchase_domain, get_domain_purchase_pay_link, get_checkout_link; buy_ai_tokens, get_ai_tokens_pay_link). brainstorm_names is explicitly a duplicate of search_brandable_domains, so the set has multiple confusing overlaps despite detailed descriptions.

Naming Consistency4/5

Most tool names follow a predictable snake_case verb_noun pattern (appraise_domain, check_domain_availability, purchase_domain, screen_trademark_conflicts). Minor deviations like brainstorm_names, register_domain_spt, and get_checkout_link break the pattern slightly but remain readable and recognizable.

Tool Count3/5

Sixteen tools is right at the boundary where a tool set starts to feel heavy. Many tools are legitimately needed for discovery, purchasing, and payment routing, but the duplicate name-generation tool and the multiple payment-route variants add unnecessary bulk.

Completeness4/5

The core domain lifecycle is well covered: search/discovery, availability checks, details, appraisal, trademark screening, registrant contact, and both fresh registration and marketplace purchase paths are present. Minor gaps exist around post-purchase management, account balance visibility, and offer submission, but the main user journey has no significant dead ends.

Resources