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log_visit

Log restaurant visits booked outside the system to maintain complete dining history and enable future reviews. Record date, party size, companions, and cuisine to enhance personalized recommendations.

Instructions

Log a restaurant visit (for places booked outside the system). Visits booked through this assistant are logged automatically.

Args: restaurant_name: Name of the restaurant you visited. date_str: Date of visit, e.g. "2026-02-10" or "last Tuesday" (default: today). party_size: Number of diners. companions: Names of who you dined with, e.g. ["Alice", "Bob"]. cuisine: Type of cuisine, e.g. "italian", "mexican".

Returns: Confirmation with visit ID for adding a review.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
restaurant_nameYes
date_strNo
party_sizeNo
companionsNo
cuisineNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so full burden on description. It discloses the mutation (logging) and return value (visit ID), but lacks details on idempotency, duplicate handling, or persistence guarantees.

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

Conciseness4/5

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

Structured Args/Returns format is appropriate for 0% schema coverage. Every section earns its place, though the docstring-style format is slightly verbose compared to prose.

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

Completeness4/5

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

Complete given constraints: handles zero schema coverage via Args block, references output schema value (visit ID), and connects to sibling functionality (adding reviews). Could explicitly reference rate_visit tool.

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

Parameters4/5

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

With 0% schema description coverage, the Args section fully compensates by documenting all 5 parameters with semantic meaning and examples (e.g., date formats, companion array structure). Minor deduction for slight discrepancy between schema default (null) and described default ('today').

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

Purpose5/5

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

Description opens with specific verb 'Log' and resource 'restaurant visit', immediately clarifying scope with parenthetical '(for places booked outside the system)' that distinguishes it from automatic logging.

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?

Explicitly defines when to use ('booked outside the system') and implies when not to use ('Visits booked through this assistant are logged automatically'), though it doesn't explicitly name alternative tools like make_reservation.

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

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