fetch_structured_data

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

No annotations are provided, so the description carries the full behavioral disclosure burden. It only states extraction capabilities and the existence of persistent sessions via tab_id; it does not disclose whether a new tab is opened when tab_id is omitted, whether the tab remains open afterward, whether the operation is read-only, or how sessions are cleaned up. These are material side effects for an agent to invoke the tool safely.

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 short sentences with no filler. The core capability is front-loaded, followed by a scannable list of extractable data types and one sentence about session reuse. 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?

With no annotations and no output schema, the agent learns what can be extracted but not what the return payload looks like, what side effects occur, or when this tool is the right choice among thirteen browser-related siblings. For a tool that can create or reuse persistent browser sessions, this leaves too much to inference.

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 already documents all four parameters with 100% coverage, including optionality, defaults, and the relationship between url and tab_id. The description adds little beyond restating the tab_id concept ('Supports persistent sessions via tab_id'), so it does not meaningfully extend the schema's parameter semantics.

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 states a specific action ('Extract structured data') on a precise resource ('a web page') and enumerates the concrete data types it returns: JSON-LD, OpenGraph tags, meta tags, tables, headings, and links. That list clearly distinguishes it from sibling tools like fetch_readable, fetch_page, and extract_links, which have narrower or different extraction scopes.

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 makes the tool's domain clear and mentions the persistent-session tab_id option, so an agent can infer when structured-data extraction is wanted. However, it never explicitly says when to prefer this tool over fetch_readable, fetch_page, or extract_links, nor does it explain when to supply tab_id versus url. The guidance is implied rather than explicit.

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