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. It mentions generating data from web content but doesn't specify output format, potential rate limits, authentication needs, or whether it performs network requests. For a tool that likely fetches and processes external content, this lack of detail is a significant gap.

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 functionality without unnecessary words. Every part of the sentence ('Generate word frequency analysis and word cloud data from web content') directly contributes to understanding the tool's purpose.

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 complexity (web content analysis with 4 parameters), no annotations, and no output schema, the description is minimally adequate. It states what the tool does but lacks details on behavior, output format, and usage context. For a tool that likely involves external requests and data processing, more completeness would be beneficial.

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?

Schema description coverage is 100%, with clear documentation for all four parameters (url, maxWords, minLength, useCache). The description adds no additional parameter semantics beyond what's in the schema. According to the rules, when schema coverage is high (>80%), the baseline score is 3 even without param info in the description.

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: 'Generate word frequency analysis and word cloud data from web content.' It specifies the action (generate), the resource (word frequency analysis and word cloud data), and the source (web content). However, it doesn't explicitly differentiate from sibling tools like 'extract_keywords' or 'analyze_readability,' which might have overlapping functionality.

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. With many sibling tools focused on content analysis (e.g., 'extract_keywords,' 'analyze_readability,' 'summarize_content'), there's no indication of specific use cases, prerequisites, or exclusions. The agent must infer usage based on the name and description alone.

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