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 states the tool 'reads' data (implying a read-only operation) and mentions it 'can be a cache lookup' with 'more reliable than scraping' characteristics. However, it doesn't address important behavioral aspects like rate limits, authentication needs, error conditions, or what 'structured data' specifically means in the return format.

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 extremely concise with three sentences that each serve a distinct purpose: stating the core function, specifying the input requirement, and providing reliability context. There's zero wasted language, and the information is front-loaded with the primary purpose first.

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 single-parameter read tool with no annotations and no output schema, the description provides adequate but incomplete context. It covers the basic purpose, input requirement, and reliability advantage, but lacks details about the return format, error handling, or performance characteristics. Given the simplicity of the tool (one parameter, read operation), this is minimally sufficient 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 schema has 0% description coverage for its single parameter 'url'. The description adds meaningful context: 'Requires a valid youtube profile URL,' specifying the parameter's purpose and format requirement. However, it doesn't provide examples of valid URL formats or clarify what constitutes a 'youtube profile URL' versus other YouTube URLs. With only one parameter and some added semantics, this meets the 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 youtube profiles data.' It specifies the verb ('read'), resource ('youtube profiles data'), and key characteristic ('structured'). However, it doesn't explicitly differentiate from sibling tools like 'web_data_youtube_videos' or 'web_data_youtube_comments' beyond the resource type.

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 for when to use this tool: 'Requires a valid youtube profile URL.' It also offers comparative guidance: 'This can be a cache lookup, so it can be more reliable than scraping,' which implicitly suggests using this over scraping tools for reliability. However, it doesn't explicitly name alternative tools or specify when NOT to use it.

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