extract_articles

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the basic extraction intent but does not explain what 'likely' means, whether the page is modified, whether it scrolls, or what limitations exist. No safety or side-effect information is provided.

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 a single concise sentence that clearly states the primary function. It is front-loaded with the verb and resource, with no wasted words or redundant information.

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 lack of annotations, minimal parameter documentation, and the presence of sibling extraction tools, the description is incomplete. It provides no usage context, parameter semantics, or expected output details beyond what an output schema might convey.

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 description coverage is 0%, and the description fails to explain the 'device' parameter or the 'max_items' parameter. The description only references 'current browser page,' which indirectly hints at 'device' but provides no explicit meaning or usage guidance for the required parameter.

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 'Extract' with a clear resource: 'likely visible article/headline candidates from the current browser page.' It distinguishes itself from sibling tools like extract_visible_text (general text) and read_news (news-specific) by focusing on article/headline detection in the current page.

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 does not state when to use this tool over alternatives such as extract_visible_text or get_elements. No exclusions or alternative tools are mentioned, leaving the agent without guidance on selecting this tool in contexts where other extraction tools might be more appropriate.

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