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

The annotations show an open-world, non-read-only action, and the description adds crucial behavioral context: this transmits user contact details and cluster information to the vendor team, requires user-visible disclosure and consent, and forbids fabricated details. That is exactly the kind of external-effect behavior an agent must understand before calling.

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 tight sentences, front-loads the purpose, then lists the preconditions. Every sentence carries operational value with 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 high-stakes external submission tool, the description covers what will be sent, the required consent workflow, and the prohibition on fabricated details, while the schema fully documents all fields. It could mention post-submission behavior or expected confirmation, but the essential invocation context is present.

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 coverage is 100%, so parameter meanings are already documented. The description still adds useful semantics for the summary field and user_confirmed by specifying that summary should include benchmark, cost, or compatibility results and confirmation must follow explicit user agreement.

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 names a specific action and resource: sending contact details and cluster summary to the XportL enterprise team to arrange a technical assessment or demo deployment. It clearly distinguishes this outreach action from the analytical sibling tools.

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?

It gives explicit pre-call requirements: collect the user's details and summary, show exactly what will be sent, and obtain explicit agreement. It also states a hard when-not condition: never call without agreement or with made-up details, though it does not explicitly compare against sibling tools.

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