Check current pricing and payment requirements for the BaaS scrape engine.
Returns pricing info, supported networks, and payment instructions.
No authentication required.
Returns:
Current pricing details and payment instructions.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds useful behavioral context beyond annotations by explicitly stating that no authentication is required and by listing what the tool returns (pricing info, supported networks, payment instructions). No contradiction with 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 short and front-loaded with the core purpose. The final 'Returns:' line is somewhat redundant with the preceding sentence, but it is not verbose enough to cause confusion or dilute the message.
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 that this is a zero-parameter, read-only, idempotent tool with an output schema, the description covers everything an agent needs: what it does, what it returns, and that no authentication is required. Nothing material is missing.
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, so the schema carries no meaningful parameter information. The description correctly focuses on the query's result rather than inputs; a baseline of 4 is appropriate because there is nothing for the description to clarify.
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 specific verb ('Check'), a clear resource ('current pricing and payment requirements'), and the scope ('BaaS scrape engine'). It is immediately distinguishable from siblings like scrape and server_status because the topic is pricing, not scraping or server 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 clearly establishes the context for use: whenever current pricing, payment requirements, or supported networks are needed. It does not explicitly name alternatives or exclusions, but the purpose is narrow enough that no confusion with the sibling tools is likely.
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 purpose: get_pricing handles payment info, scrape performs the core scraping, and server_status reports engine health. There is no overlap or ambiguity between them.
get_pricing and scrape follow a simple verb-oriented pattern, but server_status deviates by using a noun_noun form instead of a verb-based name (e.g., get_status). The inconsistency is minor and does not hinder readability.
Three tools is a well-scoped set for a BaaS scraping API: one to check pricing, one to scrape, and one to monitor server health. Each tool earns its place without unnecessary bloat.
Core scraping workflows are fully covered with flexible output formats and options. Minor gaps exist, such as no batch scraping or explicit API-key management, but these are not essential for the stated purpose and can be worked around.