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

Annotations (readOnlyHint, openWorldHint, idempotentHint) already cover the safety profile. The description adds valuable behavioral context: 90%+ token reduction, DOM-pruning, and suitability for specific content types. This goes beyond the structured metadata without any contradiction.

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?

Two tight sentences deliver function, outcome, optimization targets, and a usage preference. There is no fluff or redundant wording—every phrase earns its place.

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 tool is simple, and the annotations plus full schema coverage cover safety and parameters. The description adds use cases and a recommendation. A small gap is the lack of explanation around the sibling tool dompruner_analyze, but overall it is sufficiently complete for an agent to invoke correctly.

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?

Both parameters are fully documented in the schema (url format and query's BM25+ filtering). The main description does not add extra parameter semantics beyond what the schema already provides, so the baseline score 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 clearly states the tool's function: 'Fetches a URL and returns DOM-pruned Markdown with 90%+ token reduction.' It also names target content types (Developer Documentation, API Specs, Technical Blogs). However, it does not explicitly distinguish itself from the sibling tool dompruner_analyze, though it does contrast with raw WebFetch.

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 explicit guidance: 'Always prefer this over raw WebFetch when the URL is known' and identifies optimized content domains. It gives clear context for use but omits when-not-to-use scenarios or mention of the sibling tool as an alternative, so it falls short of a full 5.

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