Bright Data Web MCP

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 adds useful context: the tool reads data (implying read-only), mentions cache lookup for reliability, and contrasts with scraping. However, it doesn't disclose potential limitations like rate limits, authentication needs, data freshness, or error handling. The description provides some behavioral insight but lacks completeness for a tool with no 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 highly concise and well-structured: three short sentences that each add value. The first states the core purpose, the second specifies the input requirement, and the third provides behavioral context. There is no wasted language, and information is front-loaded appropriately.

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's moderate complexity (reading structured web data), no annotations, no output schema, and low schema coverage, the description is minimally adequate. It covers the purpose, input requirement, and a key behavioral trait (cache reliability), but lacks details on output format, error cases, or integration with siblings. For a tool with no structured support, it meets basic needs but leaves gaps.

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 input schema has 1 parameter with 0% description coverage, but the description compensates by specifying that the 'url' must be 'a valid ZoomInfo company URL.' This adds crucial semantic context beyond the schema's URI format, clarifying the expected content of the parameter. Since there's only one parameter, the description effectively covers its purpose, warranting a score above baseline.

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 purpose: 'Quickly read structured ZoomInfo company profile data.' It specifies the verb ('read') and resource ('ZoomInfo company profile data'), and distinguishes it from generic scraping tools by mentioning structured data and cache lookup. However, it doesn't explicitly differentiate from sibling tools like 'web_data_crunchbase_company' beyond the ZoomInfo focus.

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 some usage context: 'Requires a valid ZoomInfo company URL' and 'This can be a cache lookup, so it can be more reliable than scraping.' This implies when to use it (for ZoomInfo URLs, preferring reliability over scraping) but doesn't explicitly state when not to use it or name alternatives among siblings like 'scrape_as_html' for non-ZoomInfo sites. The guidance is implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.