card_statusPoll a card purchase started by card_buy (free). done=true when status is 'ready' (fetch details with card_get) or 'failed' (payment auto-refunded — see refund_status).
| Name | Required | Description | Default |
|---|---|---|---|
| card_id | Yes | operation_id / card_id returned by card_buy |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It discloses that polling is free, that done=true only when the purchase is ready or failed, and that a failed purchase triggers an automatic refund accessible via refund_status. This gives the agent clear expectations about the tool's state transitions and side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one dense sentence that front-loads the core action ('Poll a card purchase') and efficiently packs in status conditions and next steps. No word is wasted; it achieves high clarity without verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter polling tool with no output schema, the description covers the essential behaviors: what to poll, when it's done, what the statuses mean, and what to do next (fetch details or check refund). It is complete enough for an agent to use the tool correctly in the card purchase workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 100% coverage for the single parameter card_id, including its origin from card_buy. The tool description reinforces this by referencing card_buy, but does not add new semantic meaning beyond the schema. Hence, baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool polls a card purchase started by card_buy, using the specific verb 'poll' and the resource 'card purchase'. It differentiates from sibling tools by framing this as the status-checking step between purchase and detail retrieval (card_get).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly specifies when to use this tool: after card_buy, to monitor completion. It also provides workflow guidance: when done with status 'ready', use card_get for details, and when 'failed', see refund_status for auto-refund information. This effectively distinguishes it from alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.