extract_structured

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

With no annotations present, the description carries the behavioral burden, and it delivers: it discloses auto-deduplication, empty-item filtering, and direct-text-only extraction. These are meaningful behaviors beyond what the input schema alone implies, though it could still clarify what happens on zero matches or how the output is shaped.

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 sentences with no filler: the core action is front-loaded, key behaviors are listed compactly, and the prerequisite tool usage is placed at the end. Every clause 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 rich schema covers all parameters, and the description adds the critical prerequisite (detect_content_pattern) plus key data-shaping behaviors. It does not explicitly describe the return format or no-match behavior, and there is no output schema, so it stops just short of fully 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?

Schema description coverage is 100%, so the schema already documents all five parameters and their defaults. The description reinforces direct-text and deduplication behavior but does not add new parameter-level meaning beyond what the schema provides.

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 verb ('Extract'), a clear resource ('structured data from repeated elements'), and gives concrete examples ('cards, rows, listings'). This makes it easy to distinguish from generic scraping tools like scrape_page or extract_table without needing to inspect schemas.

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 explicitly tells the agent to run detect_content_pattern first to find the correct selectors, which is actionable guidance. It does not enumerate when to avoid this tool in favor of extract_table or scrape_page, but the scope ('repeated elements') provides enough context for most selection decisions.

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