check_creditsReturn the remaining verification credit balance for the account that owns the API key. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| notice | No | Present only when the balance is low or empty | |
| credits | Yes | Remaining verification credits on the account | |
| success | No | ||
| purchaseUrl | No | Where the user can buy more credits |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the operation as read-only, idempotent, and non-destructive. The description adds meaningful context by specifying 'Free', indicating the call does not consume verification credits, and clarifies the account scope tied to the API key. This goes beyond the structured annotations.
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 concise sentence that front-loads the key action and resource, then adds the account context and cost implication. No wasted words.
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 zero-parameter read-only tool with a full output schema available and annotations covering safety, the description is complete. An agent can confidently invoke this tool without additional information.
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?
There are zero parameters and the schema is trivially empty, so the baseline is 4. The description adds relevant context by explaining that the balance is tied to the API key's account, which makes the absence of parameters sensible and complete.
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 states a clear verb ('Return'), a specific resource ('remaining verification credit balance'), and the owning context ('the account that owns the API key'). It is immediately distinguishable from sibling tools like verify_email and verify_bulk, which perform verification operations rather than balance checks.
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 provides clear context about what the tool does, but it does not explicitly state when to use it relative to alternatives or mention any exclusions. Usage is implied rather than directly guided, though the purpose is narrow enough that ambiguity is low.
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 has a clearly distinct responsibility: real-time single verification, background bulk verification, bulk job status polling, credit balance lookup, and email discovery. The overlap between verify_email and verify_bulk is resolved by descriptions of real-time vs async batch processing.
All tool names follow a consistent verb_noun pattern using lowercase snake_case: verify_email, verify_bulk, check_bulk_status, check_credits, find_email. The naming convention is uniform and predictable.
Five tools is well-scoped for an email verification service: single verification, bulk verification, status polling, credit tracking, and person email discovery. No redundant tools exist and each earns its place.
The set covers the core email verification lifecycle well, including single and bulk paths plus credit management. The only minor gap is that detailed bulk result files are accessible via the dashboard rather than the API, and there is no cancel/delete operation for bulk jobs.