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

Annotations already declare readOnly/closed-world/idempotent, and the description adds meaningful context beyond them: 'opens nothing by itself' warns the agent the tool triggers no UI action, and the API note explains why browser automation is required. It does not contradict any annotation.

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 critical fact (returns instructions, opens nothing) is packed mid-sentence inside a run-on that also carries audience boilerplate and a dated API trivia parenthetical ('checked 23 Oct 2026'). It is not poorly written, but the most decision-relevant content is not front-loaded.

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 zero-parameter, no-output-schema tool, the description covers what the agent gets back (step-by-step screens/buttons/fields), that no side effect occurs, and what to do next. Only the exact shape of the returned guide and any prerequisites (e.g. a connected Cloud Browser) go unstated.

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?

There are zero parameters, so there is nothing for the description to disambiguate; the schema baseline applies. No parameter semantics are needed or missing.

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 the resource (orders in the user's own Billetto account) and, crucially, discloses that the tool does not actually fetch data but returns step-by-step instructions with screens, buttons and fields. That resolves the tension with the 'list orders' name, though the opening marketing phrasing ('from ChatGPT, Claude or any AI agent') delays the real purpose.

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 the follow-up path explicitly ('then do it with the cotlet_browser_* tools in the user's Billetto Cloud Browser'), which is real routing guidance. It never states when not to use it or how it relates to the sibling billetto_* action tools (add_order_note, refund_tickets, etc.), so selection among those is left to inference.

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