apple_contacts_stats
Get total contact count and top companies by contact count from your Apple Contacts.
Instructions
Contact count and top companies by contact count.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Get total contact count and top companies by contact count from your Apple Contacts.
Contact count and top companies by contact count.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only discloses the output (count and top companies). It omits behavioral details like whether this is a live query, a snapshot, or requires specific permissions, leaving behavioral ambiguity.
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, clear sentence with no wasted words. It is appropriately concise for a tool with no parameters.
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?
While the description covers the basic purpose, it lacks specifics such as the format of the output, how many top companies are returned, or whether the count is total or grouped. Given no output schema, these details are missing.
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?
The input schema is empty (no parameters), and schema description coverage is 100% vacuously. The description adds meaning by explaining the output semantics, which goes beyond the empty schema.
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 clearly states the tool returns 'contact count and top companies by contact count,' which is a specific verb+resource (stats on contacts) and distinguishes it from sibling tools like search or get.
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?
No usage guidance is provided. The description does not indicate when to use this tool versus alternatives such as apple_contacts_search or apple_contacts_get, leaving the agent to infer context from the name alone.
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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