Apple Mail MCP Server

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

With no annotations provided, the description carries the full burden and successfully discloses the behavioral heuristics (filters newsletters/automated emails, prioritizes direct emails with question marks). It also describes the return value (ranked list with priority hints). It omits error handling or empty-result behavior, but the core algorithm is transparent.

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 follows a clear docstring structure (summary, Args, Returns) with no wasted words. The opening sentence establishes purpose immediately, followed by behavioral details, then structured parameter documentation. Each sentence earns its place by conveying unique information not present in the structured schema fields.

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?

For a tool with 4 parameters and an output schema, the description is complete. It compensates for the 0% schema coverage with full parameter documentation, explains the ranking algorithm, and describes the return format sufficiently (acknowledging the output schema handles detailed structure).

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?

Given 0% schema description coverage, the Args section fully compensates by documenting all 4 parameters with clear semantics and helpful examples (e.g., account: 'Gmail', 'Work', 'Personal'). It explains the purpose of each parameter (mailbox to scan, days back to look) and notes defaults, effectively serving as the primary parameter documentation.

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 explicitly states the tool 'Identify unread emails that likely need a response from you,' providing a specific verb (identify) and resource (emails). It distinguishes itself from generic email listing tools (like list_inbox_emails) by detailing the specific filtering heuristics (newsletters, noreply) and prioritization logic (question marks, direct emails).

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 the tool by explaining what gets filtered out and prioritized, implying the use case (finding actionable emails vs. browsing all unread). However, it lacks explicit 'when not to use' guidance or named sibling alternatives (e.g., contrasting with get_awaiting_reply).

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