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Apple Suggest Contacts

apple_suggest_contacts
Read-onlyIdempotent

Suggests contacts from Apple data surfaces based on a query, providing completion options for clients that lack MCP completion support.

Instructions

Apple Suggest Contacts using the current Apple data surfaces. This is a completion fallback for clients without MCP completion support.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNo
countYes
domainYes
suggestionsYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.4

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds 'current Apple data surfaces' and the fallback role, which provides some context but remains vague about what data surfaces are used or how suggestions are produced. No contradiction with annotations.

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?

Two short sentences with the core purpose front-loaded and the fallback context stated efficiently. Minor redundancy with the title ('Apple Suggest Contacts') keeps it from being a 5.

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?

The presence of an output schema covers return values, and annotations cover safety, so the description only needs to explain invocation context. It does that reasonably for a fallback tool, but it leaves parameter semantics and 'current Apple data surfaces' unexplained, making it minimally adequate rather than complete.

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 0%, and the description does not explain the query or limit parameters at all. While the parameter names are somewhat self-explanatory, the description adds no meaning beyond the schema's type/default information, which is insufficient at this coverage level.

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 names a specific verb ('Suggest') and resource ('Contacts'), and the completion-fallback phrase clarifies this is for autocomplete-style lookups. It does not explicitly contrast with contacts_search_contacts, so it stops short of full sibling differentiation.

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?

The description clearly states the intended use case: completion fallback for clients without MCP completion support. This gives an explicit trigger condition, though it does not mention alternatives or when not to use this tool.

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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