get_usage
Check API usage and remaining credits. Returns current plan, subscription credits, purchased credits, and total remaining credits.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Check API usage and remaining credits. Returns current plan, subscription credits, purchased credits, and total remaining credits.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly enumerates the returned fields (current plan, subscription credits, purchased credits, total remaining credits), which is informative. It does not explicitly state read-only behavior or auth requirements, but for a zero-parameter query tool, the return specification is a strong behavioral disclosure.
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 two concise sentences, front-loaded with the primary purpose, and contains no filler or redundant information. It earns its place by stating both the action and the return details.
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 zero-parameter schema, no output schema, and no annotations, the description provides sufficient detail about the tool's behavior and return data. It is complete for an agent to understand what to expect. The only minor omission is an explicit read-only statement, but the nature of the tool makes it evident.
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 tool has zero parameters, and the schema coverage is 100% (trivially, since there are no properties). The description adds meaning by explaining what the response contains, which is valuable for an agent deciding whether to call this tool.
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's function with a specific verb ('Check') and resource ('API usage and remaining credits'), and details the return content. It distinguishes itself from sibling tools like get_billing by focusing on credits versus billing information.
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 provides clear context for when to use this tool (when you need to check API usage and remaining credits) and what it returns. It does not explicitly mention when not to use it or contrast with alternatives like get_billing, but the context is straightforward and not misleading.
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.
get_billing and get_usage overlap somewhat in describing plan/credit information, but their distinct focus on billing details vs. usage/credits keeps them separable. scrape_url and scrape_urls are clearly differentiated by singular vs. plural operation. scraper_server_status is entirely distinct. Overall, the tools are mostly distinct with only mild ambiguity between billing and usage.
Most tools follow a verb_noun pattern (get_billing, get_usage, scrape_url, scrape_urls), but scraper_server_status deviates as a noun phrase. This mixed convention is still readable and predictable, but not fully consistent.
With 5 tools, the server is well-scoped for a scraping API. It covers single/batch scraping, server status, billing, and usage without unnecessary bloat, making the count appropriate for its purpose.
The tool surface covers the core lifecycle of a scraping service: scraping (single and multiple), health monitoring, and account management (billing/usage). Minor gaps exist, such as lack of detail on plan management or job cancellation, but these are not critical for the primary use case.