MCP Web Scrape

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'extract' implies a read-only operation, the description doesn't specify whether this tool makes network requests, has rate limits, requires authentication, or what the output format looks like (e.g., structured JSON, plain text). For a tool with no annotation coverage, this leaves significant behavioral gaps.

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 a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part of the sentence ('Extract named entities', 'people, places, organizations', 'from web content') contributes directly to understanding the tool's function, with zero waste.

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 tool with no annotations and no output schema, the description is minimally adequate but incomplete. It covers the basic purpose and parameters (via schema), but lacks behavioral context (e.g., network behavior, error handling) and output details. Given the complexity of web content extraction and the absence of structured output documentation, the description should provide more guidance on what to expect.

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 100% description coverage, with clear documentation for all three parameters (url, entityTypes, useCache). The description adds no additional parameter semantics beyond what's already in the schema, such as explaining what 'web content' encompasses or how entity extraction works technically. This meets the baseline score when schema coverage is high.

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 verb 'extract' and the resource 'named entities (people, places, organizations) from web content', making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'extract_content', 'extract_keywords', or 'extract_contact_info', which also extract information from web content but focus on different data types.

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 no guidance on when to use this tool versus alternatives like 'extract_content' (which might extract full text) or 'extract_keywords' (which focuses on keywords rather than entities). There's no mention of prerequisites, use cases, or exclusions, leaving the agent to infer usage from the tool name alone.

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