extract_web_content

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

No annotations are provided, so the description carries the full burden. It discloses the core behavior (fetch HTML, convert to Markdown) but omits important traits like error handling for invalid URLs, size limits, or authentication requirements.

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 concise, consisting of two sentences that front-load the action and purpose. Every word adds value, with no redundancy.

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 simple tool with one parameter and no output schema, the description covers the main transformation but lacks details on error behavior, response format, or any limitations. It is minimally adequate but not complete.

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 input schema has one parameter 'url' with 0% description coverage. The description does not add meaning beyond the schema—it does not explain what formats are accepted, constraints, or behavior of the parameter. For a single-parameter tool with no schema descriptions, the description should compensate but fails to do so.

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 HTML and converts it to Markdown, preserving semantic tags. It uses a specific verb ('fetches') and resource ('web content'), and distinguishes from the sibling tool 'query_metrics_database' which serves a different purpose (database queries).

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 extracting web content into Markdown, but lacks explicit guidance on when to use versus alternatives, prerequisites (e.g., network access), or when not to use (e.g., for non-HTML content). No alternatives are discussed.

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