Check the BaaS engine health and operational status.
Returns browser status, uptime, x402 payment mode, and context count.
Returns:
Server health and diagnostic information.
| 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 establish read-only, idempotent, and non-destructive behavior. The description adds value by naming what the agent will actually receive: browser status, uptime, x402 payment mode, and context count. 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 first sentence is strong and the return-field list is useful, but the final 'Returns: Server health and diagnostic information' repeats what the preceding sentence already stated. The description is compact but not every sentence earns its place.
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?
With zero parameters, strong safety annotations, an output schema, and unrelated siblings, the description covers everything an agent needs to invoke and interpret this tool correctly. It names the expected diagnostic fields and leaves no meaningful gap.
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 there are no parameter semantics for the description to clarify. The baseline of 4 for a parameterless tool is appropriate, and the description sensibly focuses on outputs instead.
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 action ('Check') and a specific resource ('BaaS engine health and operational status'). It also enumerates concrete return fields, making its purpose unambiguous and clearly distinct from the unrelated sibling tools get_pricing and scrape.
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 makes the usage context clear: this is a health-and-status diagnostic call. It does not explicitly name alternatives, but none of the siblings are plausible substitutes, so no exclusion is strictly needed.
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.