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Glama

Palmyr

by ai.palmyr

Buy prepaid Visa card

card_buy

Buy a USA prepaid Visa card loaded with EXACTLY the requested balance ($5–$1000). Dynamic x402 price = amount + fee (3% min 0.50 USDC) — the 402 instructions carry the exact total. Returns 202 with an operation_id: poll card_status until ready (~10s), then fetch the number with card_get. US merchants only; non-reloadable (spend across transactions until depleted); max 6 cards per agent per rolling 24h (issuer limit).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amountYesUSD balance to load on the card (min $5, max $1000, whole cents)
paymentNobase64 x402 payment payload (X-PAYMENT); omit on first call to receive payment instructions

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations provided, the description carries full burden and does an excellent job. It discloses the fee structure (3% min 0.50 USDC), the exact total in 402 instructions, the asynchronous flow (returns 202, requires polling), the non-reloadable nature, and the issuer limit. All critical behaviors are surfaced.

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 a single dense paragraph, but every sentence serves a purpose: defining the product, explaining pricing and flow, and listing restrictions. It is front-loaded with the core purpose and efficiently structured with 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 complex async purchase tool with no output schema, the description fully covers the lifecycle: payment instruction, total cost, operation_id, polling, and retrieval via card_get. It also references sibling tool names for the next steps, making the overall flow complete.

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?

Schema coverage is 100% with both parameters already described. The description adds value by explaining how 'amount' translates to the exact loaded balance and how 'payment' fits into the x402 flow, including the fee calculation. This goes beyond the schema without redundancy.

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 'Buy a USA prepaid Visa card', using a specific verb and resource, and immediately clarifies the exact balance range ($5–$1000). It clearly distinguishes from sibling tools like card_get, card_status, and card_list by focusing on the purchase action.

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?

It provides explicit instructions: the dynamic pricing formula, the 202 response with operation_id, polling via card_status (~10s), then fetching the card with card_get. It also states constraints (US merchants only, non-reloadable, max 6 per 24h), giving clear context on when and how to use the tool.

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
Disambiguation5/5

Each tool targets a distinct resource and action, clearly separated by domain prefixes (card_, email_, phone_, tiktok_). The only potential overlap is phone_read_messages vs wait_for_otp, but wait_for_otp is specifically for OTP extraction and is described as a replacement for hand-rolled polling, making the boundary clear. Status pollers are also domain-specific (card_status, tiktok_connect_status, tiktok_operation_status) and not ambiguous.

Naming Consistency5/5

All tool names follow a consistent snake_case convention with domain-first prefixes (e.g., card_buy, email_send, tiktok_post, phone_temp_number). Even less common names like wait_for_otp and i402_plan are descriptive and stylistically consistent. There are no mixed conventions or vague verbs.

Tool Count4/5

33 tools is above the typical 3-15 range, but the server covers a broad multi-domain purpose (cards, compute, domains, email, phone, TikTok, Twitter, orchestration). Each domain has a focused and coherent set, so the count feels justified rather than bloated. It is slightly high, but not excessively so.

Completeness3/5

Coverage is solid for email, phone, and TikTok, with full lifecycle operations (create, read, extend, delete/cancel where applicable). However, there are notable gaps: compute has only deploy (no list/stop/delete), domains have only check/register (no list/delete), and Twitter has only post (no read/manage). These gaps could force agents to work around missing resource management.

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