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list_starred_emails

Retrieve all starred emails from your IMAP account, organized by folder with key details like subject, sender, and date for quick review.

Instructions

List all starred (flagged) emails across all folders, grouped by folder. Returns an array of {id, subject, from, date} objects sorted newest-first. The id is a globally unique identifier — use it with fetch_email_content to read the full email.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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 effectively describes the return format (array of objects with specific fields), sorting order (newest-first), grouping behavior (by folder), and how to use the output (id for fetch_email_content). It doesn't mention rate limits, authentication needs, or pagination, but covers core behavior well.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured in two sentences: the first states purpose and output format, the second explains the id's usage. Every sentence adds value without redundancy, and key information (what it does, what it returns, how to use the output) is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only listing tool with 0 parameters and no output schema, the description is quite complete. It explains the filtering (starred), grouping (by folder), return format, sorting, and how to use the result. It doesn't cover potential edge cases like empty results or error conditions, but provides sufficient context for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, maintaining focus on the tool's purpose and output. This meets the baseline for zero parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('List all starred emails'), resource ('emails'), and scope ('across all folders, grouped by folder'), distinguishing it from sibling tools like list_emails_24h or list_emails_from_sender which filter differently. It explicitly mentions the filtering criteria (starred/flagged) and organizational grouping.

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 provides clear context for when to use this tool (to retrieve starred emails grouped by folder) and implicitly suggests an alternative (fetch_email_content for full content using the returned id). However, it doesn't explicitly state when NOT to use it or compare it directly to other list_emails_* siblings beyond the starred filtering.

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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