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 states the action ('detect') but doesn't explain how it works (e.g., whether it analyzes text from the URL, handles errors, or has rate limits). For a tool with no annotations, this is a significant gap, as it lacks details on performance, reliability, or side effects.

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: 'Detect the primary language of web page content.' It's front-loaded with the core purpose, has zero wasted words, and is appropriately sized for a straightforward tool, making it easy to parse quickly.

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 low complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks context on usage, behavior, or output. Without annotations or an output schema, the agent might struggle with how to interpret results or handle edge cases, leaving room for improvement.

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 'url', 'confidence', and 'useCache'. The description doesn't add any parameter-specific information beyond what's in the schema. According to the rules, with high schema coverage (>80%), the baseline is 3, as the schema does the heavy lifting without needing extra details 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: 'Detect the primary language of web page content.' It specifies the verb ('detect') and resource ('language of web page content'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'translate_content' or 'classify_content', which might involve language-related operations, so it doesn't reach the highest score.

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. It doesn't mention sibling tools like 'translate_content' (for translation after detection) or 'classify_content' (which might involve language classification), nor does it specify prerequisites or exclusions. This lack of context leaves the agent without clear usage instructions.

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