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

The annotations provide readOnlyHint=true, and the description adds meaningful behavioral context beyond that: it blocks private/cloud-metadata addresses, re-validates redirect hops, returns cleaned text rather than raw HTML or binary, and warns about JS-heavy pages. This gives the agent a strong safety and expectations model.

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 well-structured with clear sections for purpose, use cases, limitations, and alternatives. Every sentence adds value, with no filler or repetition, and the most important scope information is front-loaded.

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 an output schema, full input schema descriptions, and a readOnly annotation, the description covers everything an agent needs: what it returns, when to use it, safety restrictions, and behavioral limitations. Nothing critical is missing.

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%, so the input schema already explains both 'url' and 'max_chars'. The description does not add parameter-level details, but it also doesn't need to; the schema carries the burden and the baseline of 3 applies.

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 names a specific verb ('Fetch'), a specific resource ('web page'), and the exact deliverable ('main text content, cleaned of markup'). It also distinguishes itself from sibling tools like web_search and get_token_price by framing when URL-based retrieval is appropriate.

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 explicitly states when to use the tool ('known URL's content is needed and structured tools cannot answer') and provides alternatives with routing guidance ('prefer web_search' for general lookup, 'get_token_price' for token prices). This is clear, actionable, and leaves little to inference.

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