Place a guest into a designated seat by providing guest, seat, table, and seating chart UUIDs.
Assign a guest to a specific seat in a seating chart
| Name | Required | Description | Default |
|---|---|---|---|
| seat_uuid | Yes | Seat UUID from get_seating_chart | |
| guest_uuid | Yes | Guest UUID from list_unseated_guests | |
| table_uuid | Yes | Table UUID from get_seating_chart | |
| seating_chart_uuid | Yes | Seating chart UUID from list_seating_charts |
Changes observed during successful MCP inspections.
v2.0.0Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"v1.4.2Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations only state destructiveHint=false, so the description carries the burden of disclosing behavioral details. It does not explain what happens if the seat is already occupied, whether the guest is moved from a previous seat, or whether the assignment overwrites existing data. The description adds no behavioral context beyond the tool's name.
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 a single, front-loaded sentence with no filler. Every word contributes to understanding the core action, and there is no unnecessary repetition of the schema or annotations.
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 mutation tool with four required parameters and no output schema, the description is too thin to be contextually complete. It omits workflow context, side-effect behavior, and any guidance about seat availability or reassignment, leaving important decisions to inference.
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% and each parameter references its source (e.g., 'Seat UUID from get_seating_chart'), so the structured schema already explains parameter semantics. The description does not add additional parameter-level meaning, which matches the baseline score of 3.
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 uses a specific verb ('assign') and resource ('guest' to a 'specific seat' in a 'seating chart'), clearly distinguishing it from sibling tools like add_guest or invite_guest_to_event. It communicates exactly what operation the tool performs without ambiguity.
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?
The description provides no guidance on when to use this tool, what preconditions exist, or how it relates to alternatives like get_seating_chart, list_unseated_guests, or remove_guest. An agent must infer the proper workflow from parameter descriptions alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.