search_contacts

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the search functionality, partial matching support, and return format, but doesn't mention performance characteristics, rate limits, authentication requirements, or error conditions. The behavioral information is adequate but not comprehensive.

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 well-structured and front-loaded with the core purpose, followed by parameter details and return format. Every sentence adds value with no redundancy. The bullet-point formatting for Args and Returns enhances readability without unnecessary verbosity.

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?

Given the tool's moderate complexity (search with two parameters), no annotations, and the presence of an output schema (which covers return values), the description is complete enough. It explains what the tool does, how to use it, parameter semantics, and references the return structure without duplicating output schema details.

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 schema has 0% description coverage, so the description must compensate. It provides clear semantic meaning for both parameters: 'query' is explained as phone number or email with partial matching, and 'limit' is explained as maximum results with default value. This adds significant value beyond the bare schema, though it doesn't cover edge cases like query formatting.

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 searches for contacts/handles in the iMessage database using phone numbers or email addresses, distinguishing it from sibling tools like search_messages (which searches message content) and lookup_contact (which appears to be a different lookup mechanism). The verb 'search' and resource 'contacts/handles' are specific and unambiguous.

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?

The description provides clear context for when to use this tool (searching by phone number or email address with partial matching), but it doesn't explicitly state when not to use it or mention alternatives like lookup_contact. The context is sufficient for basic usage but lacks comparative guidance against siblings.

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