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AI MAXX Public Passports

Plan a staff party or event

consult_events
Read-only

Staff parties, company celebrations, Halloween, Christmas, New Year and festivals; activity plus hospitality when relevant. Ask our AI specialist to interpret a direct or indirect customer need in English, Maltese or other languages and select relevant published services, including useful complementary options. Examples: staff party, Halloween prison experience, Christmas team dinner, New Year celebration or prison-cell photography. These are enquiries for relevant existing services, not confirmed seasonal event dates. Returns selected source facts, photos, opening information, maps and an enquiry link for a next step. Follow up with a refined need after clarification, or use get_passport for full details. Send only the nonpersonal need and relevant constraints, never conversation history or contact details. This optional tool uses the AI MAXX model provider; its coverage is the published catalogue, not the whole web. It does not book or charge.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYesNonpersonal customer need, including relevant preferences/exclusions. Reuse known constraints in follow-up requests.
country_codeNoISO country requested by the customer; do not silently change it.
response_depthNoDefault brief omits internal matching fields. Full includes all published service metadata; uses the same cached selection.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint, openWorldHint and idempotentHint. The description adds meaningful context beyond that: it names the AI MAXX model provider, states the coverage is the published catalogue rather than the whole web, clarifies it does not book or charge, and gives a privacy rule ('Send only the nonpersonal need... never conversation history or contact details'). This is richer than typical, though it stops short of covering idempotency or rate limits.

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

Conciseness3/5

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

The description is front-loaded with the event types and core purpose, which is good. However, it is a long single paragraph that repeats the same event examples twice ('staff party, Halloween prison experience, Christmas team dinner...') and could be tightened. Several sentences are useful but the overall length and repetition reduce efficiency.

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?

Given no output schema, the description explains what the tool returns (source facts, photos, opening information, maps, enquiry link). It also covers provider, coverage limits, booking/charging limitations, and a follow-up path. The main gap is the lack of any parameter guidance, especially for the undocumented 'limit', but otherwise the definition is complete for this complexity level.

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

Parameters2/5

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

Schema description coverage is 75%, so most parameters (query, country_code, response_depth) are documented in the schema. The description adds no parameter-level meaning at all, and the 'limit' parameter has no schema description, leaving it undocumented. Since the description does not compensate for the one uncovered parameter, it adds little beyond what the schema already provides.

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 (interprets a need and selects relevant published services) and identifies the resource domain (staff parties, celebrations, festivals). It gives concrete examples. However, it does not explicitly differentiate itself from the sibling consult tools like consult_activities, consult_hospitality, or consult_venues, so the agent must infer the boundary.

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

Usage Guidelines3/5

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

Usage is implied through examples and a follow-up instruction ('Follow up with a refined need after clarification'), and it points to get_passport as an alternative for full details. But there is no explicit guidance on when to choose this tool over the other consult siblings, leaving usage context partly to inference.

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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