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

With no annotations, the description carries the full burden. It usefully discloses the rotating mobile-proxy fetching mechanism and the token-optimized Markdown output, which are real traits beyond the schema. It says nothing about failure modes, timeouts, JS-heavy pages, paywalls, or rate limits, so the behavioral picture is incomplete.

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?

A single sentence that front-loads the action and mechanism and closes with the return format. Nothing is padded or redundant.

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 one-parameter tool with no output schema, the description covers the mechanism and the return format, which is most of what an agent needs. It stops short of stating limitations (dynamic pages, auth-gated content, size caps) that would make it fully self-sufficient.

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?

Only one parameter (url) with 100% schema description coverage, so the schema already documents it fully. The description adds no format or syntax detail beyond what the schema provides; 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), resource (any URL), and output form (clean, token-optimized Markdown extract), so the agent knows exactly what happens. It does not name or contrast with the sibling web_research, so the differentiation is only implied by the 'extract' framing.

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?

Usage is implied by the mechanics (fetch one URL, get Markdown) but there is no explicit when-to-use vs web_research and no when-not guidance. An agent can infer this is the single-page fetch path, but must guess at the boundary with the research tool.

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