opentable_add_favorite

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

Annotations already establish that this is a mutation (readOnlyHint=false), non-destructive (destructiveHint=false), and safe to repeat (idempotentHint=true). The description adds nothing beyond that—it doesn't disclose what happens when the restaurant is already in the list, whether the restaurant must exist, or what the response looks like. The description does not contradict the annotations, but it contributes no behavioral context beyond them.

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?

One clean sentence with zero filler; the action verb is front-loaded and every word is load-bearing. It is appropriately sized for a tool with a single parameter and simple semantics.

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 one-parameter tool with annotations declaring safety, the description is minimally sufficient to make the call. However, with no output schema and no error/edge-case behavior described, an agent cannot predict outcomes for invalid IDs or duplicate favorites—a notable gap for an operation with no other structured signals.

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 0%, so the description carries the full burden for restaurant_id. It loosely maps the parameter to 'a restaurant' but doesn't explain where the ID comes from (e.g., search results), how to obtain it, or any validation expectations. The self-descriptive parameter name partially mitigates the gap, but the description barely compensates for the undocumented schema.

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 pairs a specific verb ('Add') with a concrete resource ('a restaurant' → 'the user's Saved Restaurants list'), making the operation unambiguous. The sibling set naturally includes remove_favorite and list_favorites, and the add/remove semantic contrast is implicit—but the description never names or references an alternative, so it stops short of explicit sibling differentiation.

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?

No guidance is given on when to call this tool versus opentable_remove_favorite or opentable_list_favorites. There are no conditions, exclusions, prerequisites, or alternatives mentioned anywhere in the description.

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