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

With no annotations, the description carries the full behavioral disclosure burden. It explains what the tool does with the fetched page, what output to expect (clean markdown, stripped navigation/ads, resolved links, token count), and notes that it is standalone extraction. It does not cover failure cases or URL access limits, but the core behavior is well disclosed.

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 front-loaded with the core purpose and output, then adds useful context about the sample endpoint and the content kit. The final sentence about the content kit is slightly tangential but still helpful for tool discovery, and the overall length is appropriate.

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?

Given the low complexity (one parameter, no annotations, no output schema), the description covers the essential behavior: input URL, output markdown, token count, and relationship to /search. It lacks explicit error/limitation notes, but is otherwise sufficient for an agent to select and invoke the tool.

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 coverage is 0% and the description adds almost no parameter semantics beyond the schema's 'url' string. It does not specify accepted URL schemes, formats, or constraints, and mostly restates that the tool fetches a URL. For a low-coverage schema the description should compensate more than this.

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 opens with a specific verb and resource: 'Fetch a URL and return its main article as clean markdown.' It also clearly distinguishes this from sibling tools like read_pdf by focusing on web pages, and adds distinctive details like stripping boilerplate and returning a token count.

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 gives clear context: this is for fetching a URL you already have, using the same extraction as /search on result pages. It does not explicitly state when not to use it or name alternatives like extract_structured or summarize, but the intended use case is reasonably clear.

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