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

With no annotations, the description carries the full behavioral burden. It helpfully discloses exact cost ($0.020 USD) and that the tool is not covered by Pro subscription, but says nothing about output, processing behavior, or error conditions.

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?

Three short sentences, each carrying distinct information: what the tool is, its cost, and its subscription status. It is front-loaded and has no filler.

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?

For a low-complexity alias tool with one fully documented parameter, the description provides the key operational facts: it routes to text.structure deep mode, its price, and its subscription exclusion. It is nearly complete, though it still relies on the sibling tool's definition to explain the underlying behavior.

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 schema fully documents the single 'text' parameter, including minLength, maxLength, and purpose. The description adds no parameter-specific meaning beyond that, so the baseline score of 3 applies when schema coverage is complete.

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 clearly states that this tool is a convenience alias for text.structure with mode='deep', which distinguishes it from its sibling text.structure. However, it does not independently explain what deep structure extraction actually does, so full clarity depends on knowing the sibling tool.

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 implies when to use it: as a convenience wrapper for deep mode. It also discloses cost and Pro-subscription exclusion, which is useful. But it gives no explicit when-not guidance or comparison to using text.structure directly with mode='deep'.

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