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

Annotations already declare readOnlyHint and destructiveHint, covering basic safety. The description adds that it returns AI-parsed JSON and references an external API, but does not mention side effects, rate limits, or error behavior. Given the annotations, the bar is lower, and the additional context is sufficient.

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, well-structured sentence that front-loads the core action and output. It avoids redundancy, includes a useful API link, and is concise with no unnecessary words.

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?

The description gives a clear idea of the output (structured JSON) with examples, and references documentation for further context. It does not explain error handling or edge cases, but for a simple fetch-and-parse tool, this is adequate. The lack of an output schema is partially compensated by the examples provided.

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 provides 100% coverage of both parameters (url and proxy_country) with descriptions. The tool description does not add extra semantic detail beyond what the schema already states, so the baseline score of 3 is appropriate.

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 fetches a web page and returns AI-parsed structured JSON, contrasting with raw HTML. It explicitly distinguishes from the sibling fetch_html tool by highlighting the structured output, making the purpose unambiguous.

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 implies usage for cases where structured data is needed by stating 'instead of raw HTML' and listing example content types (product details, article content, listings). However, it does not explicitly name sibling tools or provide precise conditions for when to choose this over google_search or list_elements, so it falls short of fully explicit guidance.

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