List frequent email senders to see who you contact often. Filter by recent days or include Junk/Trash folders.
List most frequent email senders. Helps identify who you communicate with most.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum senders to return (default 30) | |
| days_back | No | Only count emails from last N days (0 = all time) | |
| include_junk | No | Include senders from Junk/Trash folders (excluded by default) |
Changes observed during successful MCP inspections.
v3.0.8Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It implies a read/aggregation but doesn't disclose return shape (senders plus counts?), whether Junk is excluded by default, or any ordering semantics beyond 'most frequent'. Only the ranking behavior is hinted at.
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?
Two short sentences, front-loaded with the primary action and followed by a single clarifying purpose line. No filler or redundancy; every sentence earns its place.
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?
Parameters are fully covered by the schema, but with no output schema the description omits what the result looks like (e.g., sender + frequency, ordering). For a ranking tool this leaves a modest gap an agent must infer.
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?
Schema description coverage is 100%, so all three parameters (limit, days_back, include_junk) are already fully documented in the schema. The description adds no parameter-level detail beyond what the schema provides, making the baseline 3 correct.
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?
States a specific verb and resource: 'List most frequent email senders', which is a distinct aggregation over the mail corpus rather than a message-level sibling like mail_search or mail_recent. The purpose is clear without needing the schema, though it does not explicitly call out how it differs from related mail tools.
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 phrase 'Helps identify who you communicate with most' implies the use case (relationship/frequency analysis) but gives no explicit when-to-use versus alternatives and no exclusions or prerequisites. Usage is implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.