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Save a preference

set_preferences

Stores lasting dining preferences such as seating windows, party size, private room, walking limit, budget, and notes so future restaurant searches and bookings use them by default.

Instructions

Saves a lasting preference the user stated, used as the default for later searches and bookings: seating windows, party size, private room, walking limit, budget, or a free-text note.

Input Schema

NameRequiredDescriptionDefault
noteNoAnything else to remember, e.g. "client is vegetarian", "avoid 焼肉".
partyNo
purposeNobusiness (default) or personal.business
lunch_toNo
dinner_toNo
lunch_fromNo
dinner_fromNo
private_roomNo
budget_max_yenNo
max_walk_minutesNo
make_default_purposeNoUse this purpose when a request does not say.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already establish that this is a non-destructive write operation. The description adds useful behavioral context by explaining that the saved value becomes a default for later searches and bookings, but it omits critical mutation semantics such as whether omitted fields are cleared or whether existing preferences are merged or replaced.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence states the action and effect without filler. The enumerated fields are dense but appropriate for orienting the agent quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 11-parameter write tool with no output schema and low schema coverage, the description covers purpose and persistence but leaves important gaps: whether this replaces or merges existing preferences, what happens to omitted fields, and how the time-window parameters are formatted beyond the schema patterns.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is low at 27%, so the description must compensate. It does map several parameter groups to natural-language concepts (seating windows, party size, private room, walking limit, budget, note), but it does not explain formats, units, or the lunch/dinner time distinction beyond what the parameter names already imply.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb (saves) and resource (lasting preference) and enumerates the kinds of preferences stored. It clearly distinguishes saving from reading preferences, though it does not explicitly name get_preferences as the read counterpart.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear usage context: save when the user states a lasting preference that should become the default for later searches and bookings. It does not state when not to use it or mention alternatives, which keeps it short of a 5.

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