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leeguooooo

MCP Email Service

by leeguooooo

batch_mark_read

Mark multiple emails as read in bulk to manage your inbox efficiently. Specify email IDs and folder to clear unread notifications across email accounts.

Instructions

Mark multiple emails as read

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
email_idsYesList of email IDs to mark as read
folderNoEmail folder (default: 'INBOX')INBOX
account_idNoSpecific account ID (required for safety)
Behavior2/5

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

With no annotations provided, the description carries full burden but only states the basic action without behavioral details. It doesn't mention permissions required, whether the operation is reversible, rate limits, error conditions, or what happens to emails in different folders. For a mutation tool with zero annotation coverage, this is insufficient.

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 a single, efficient sentence that states exactly what the tool does with zero wasted words. It's appropriately sized for a straightforward tool and front-loads the core functionality.

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

Completeness2/5

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

For a mutation tool with 3 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what 'mark as read' means operationally, what the response looks like, error handling, or how it differs from similar siblings. The agent would need to guess important behavioral aspects.

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

Parameters3/5

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

Schema description coverage is 100%, so all parameters are documented in the schema itself. The description doesn't add any meaning beyond what's already in the schema (e.g., it doesn't explain email ID format, folder implications, or account_id safety rationale). Baseline 3 is appropriate when the schema does the heavy lifting.

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

Purpose4/5

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

The description clearly states the verb ('mark') and resource ('multiple emails') with the specific action ('as read'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'mark_email_read' or 'mark_emails', which appear to have similar functionality, preventing a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'mark_email_read' (single email) or 'mark_emails' (unspecified marking). There's no mention of prerequisites, context, or exclusions, leaving the agent to guess based on tool names 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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