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

Annotations already declare readOnlyHint=true and non-destructive, and the description reinforces this by stating it "opens nothing by itself" — useful confirmation for an agent that might otherwise expect a mutation. It adds genuine context beyond annotations: the return shape is described (step-by-step screens/buttons/fields) and it discloses that OpenTable's official API is partner-only. Missing details on prerequisites such as login state or what happens if the reservation does not exist.

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?

Purpose and the key caveat are front-loaded, which is good. However, "from ChatGPT, Claude or any AI agent" is filler, and the trailing API note with a check date is tangential to calling the tool, so the middle section carries some dead weight.

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 tool with no output schema, the description covers the essentials: what it returns, that it performs no action, and which tools to use afterward. Gaps remain around preconditions (signed-in Cloud Browser session, what it needs to know about the target reservation).

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 tool takes zero parameters, so the description needs no parameter explanation and the baseline is 4. It correctly does not waste words on inputs, though the absence of any hint about what identifying information it will need from context is a small missed opportunity.

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+resource ("Modify a reservation in the user's own OpenTable account") and then clarifies the non-obvious mechanic that it returns step-by-step instructions rather than performing the action. It does not explicitly distinguish itself from opentable siblings such as cancel_a_reservation or add_guest_notes_and_tags, which also touch an existing reservation, so the boundary is left to inference.

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 a concrete two-step workflow: call this to get screens/buttons/fields, then execute with the cotlet_browser_* tools in the user's Cloud Browser. That names an alternative and the condition that selects it. It lacks explicit when-not guidance (e.g., use cancel_a_reservation to cancel rather than modify).

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