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

With no annotations, the description carries the full behavioral burden and it does disclose key traits beyond the schema: the data leaves the session to a third party (Bramvia), a human consultant replies by email, and there is a one-business-day turnaround. It does not state whether the request is rate-limited, whether it can be retracted, or what the agent gets back on success, so it stops short of full disclosure.

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?

Two sentences, zero filler. The action and outcome come first, and the consent precondition follows immediately, so the most safety-critical constraint is front-loaded rather than buried.

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 an unannotated mutation tool with no output schema, the description supplies the essential context: consent gating, where the data goes, and the expected human response. The remaining gap is what the tool itself returns to the agent (confirmation payload vs. error behaviour), which the agent must infer.

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 all six parameters (email, users, company, details, current_erp, user_confirmed) are already documented in the schema; this is the baseline case. The description only restates the user_confirmed: true requirement, adding no format, ordering or dependency detail beyond structured data.

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 concrete verb and resource ('Send the user's request to Bramvia'), names the recipient, the response channel (email) and an SLA (within one business day), plus the service categories covered (implementation, migration, support, quote). That is enough for an agent to distinguish it from every sibling, which are all read-only assessment/knowledge 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 an explicit invocation precondition: 'Only call it after the user has explicitly agreed to be contacted, and pass user_confirmed: true.' That is effectively a when/when-not rule. It does not name alternative tools, but no sibling overlaps with this outbound action, so the omission is minor.

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