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

Beyond annotations, the description discloses concrete operational limits: 8 seconds, 5 redirects, 768 KiB, and 50 JSON-LD blocks. It also clarifies that it fetches exactly one public HTML page, which sets useful scope expectations for an open-world read operation.

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 two compact sentences, front-loaded with the action and extracted fields, followed by clear usage context and hard limits. Every sentence contributes useful information without repetition.

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 single-parameter read-only tool with an output schema, the description provides everything needed: purpose, extracted metadata types, usage guidance, and operational limits. The output schema handles return-value documentation, so no important agent-facing context 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?

There is only one parameter and schema description coverage is 100%, so the schema already documents the URL constraints. The description adds little parameter-level detail beyond reinforcing that the page is public and HTML, making the baseline score 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 uses a specific verb and resource: it fetches one public HTML page and extracts metadata. It enumerates the exact fields returned (title, description, canonical URL, robots, Open Graph, Twitter Card, feeds, JSON-LD), which lets an agent distinguish this from body-text conversion tools.

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?

It explicitly says to use this when an agent needs page identity or structured data rather than body text, giving clear selection context. It does not name specific sibling alternatives like fetch_markdown or extract_links, so it falls short of fully explicit when-to-use/when-not guidance.

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