tiktok_accountsList the TikTok accounts the paying wallet owns, with session health (status, profile_present, hours_since_success, last_error_code) — i.e. which of your accounts are still logged in. Costs 0.001 USDC, paid per-action via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| tag | No | Only accounts carrying this tag | |
| payment | No | base64 x402 payment payload (X-PAYMENT); omit on first call to receive payment instructions |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It adds useful behavioral context: the operation is a read (list) and costs 0.001 USDC per action via x402. However, it does not disclose the payment flow (e.g., first call may return payment instructions without data) or whether the response is paginated, though the schema partially covers the payment payload. The cost disclosure is a positive, but more behavioral detail (e.g., idempotency, auth assumptions) would be beneficial.
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 a single, focused sentence that front-loads the primary action and includes only high-value context (session health fields, cost). No filler or redundancy.
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?
Given the tool is a simple list operation with 2 optional parameters and no output schema, the description provides sufficient context: it lists the key return fields (status, profile_present, hours_since_success, last_error_code) and mentions cost/payment. It could be improved by specifying the response shape (e.g., array of account objects) and the 'first call for payment instructions' behavior, but the schema covers the payment parameter. Overall, it is mostly complete for the tool's complexity.
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?
Schema description coverage is 100% for both parameters ('tag' and 'payment'), so the schema fully documents their purpose. The description adds only indirect reference to x402 via the cost statement, but does not elaborate on the parameters themselves. The baseline of 3 applies because structured data already handles parameter semantics.
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 action ('List') and resource ('TikTok accounts the paying wallet owns'), with explicit detail on what is returned (session health fields). It differentiates from siblings like tiktok_connect (which likely adds an account) and tiktok_connect_status (which checks connection status) by focusing on listing owned accounts with login health.
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?
The description implies the primary use case: checking which owned accounts are still logged in ('i.e. which of your accounts are still logged in'). It also mentions cost and x402 payment method, indicating when a payment is required. However, it does not explicitly name alternative tools or exclusions, so it provides clear context without formal when-not-to-use guidance.
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.