browser_extract_text

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

Since no annotations exist, the description carries the full burden of behavior disclosure. It states the output is 'cleaned' and includes text, links, and forms, but does not explain how cleaning works, whether scripts/styles/hidden elements are removed, or what the response structure looks like.

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?

One sentence, front-loaded with the action and resource, with no filler. Every word 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, but with no output schema and no annotations, the description should cover what the agent can expect back. It lists the content categories (text, links, forms) and signals LLM-readiness, but it leaves the exact return format unstated.

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 single selector parameter is fully documented in the schema with a default and description, so the baseline of 3 applies. The tool description itself adds no additional parameter-level meaning.

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') and a specific resource ('cleaned text, links, and forms from the page'), plus a clear purpose ('for LLM reading'). This distinguishes it from the sibling tool browser_extract_html, which presumably returns raw HTML.

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 phrase 'for LLM reading' provides clear context on when this tool is appropriate, and 'cleaned' implies a contrast with raw HTML extraction. It does not explicitly name alternatives or exclusions, so it stops short of a 5.

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