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dsouzaalan

Zapmail MCP Server

by dsouzaalan

Validate export request parameters

validate_export_request

Validate export request parameters before execution to prevent errors when exporting Zapmail data to third-party platforms.

Instructions

Validate export request parameters before execution to prevent errors.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
appsNoApps to export to
emailNoThird-party account email
passwordNoThird-party account password
appNoThird-party app name
idsNoSpecific mailbox IDs to export
containsNoFilter mailboxes containing this text
statusNoFilter by mailbox status
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool validates parameters to prevent errors, which implies a read-only, non-destructive operation, but doesn't detail what happens on validation failure (e.g., error messages, return format) or any side effects like rate limits or authentication needs. For a tool with zero annotation coverage, this is a significant gap in behavioral context.

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: 'Validate export request parameters before execution to prevent errors.' It's front-loaded with the core purpose and has zero wasted words, making it highly concise and well-structured for quick understanding.

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?

Given the complexity of 7 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the validation entails (e.g., format checks, dependency validation), what happens on success/failure, or the return structure. For a validation tool with rich parameters and no structured support, more context is needed to guide the agent effectively.

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?

The input schema has 100% description coverage, so the schema already documents all 7 parameters (e.g., 'apps', 'email', 'password'). The description doesn't add any meaning beyond this, such as explaining parameter interactions or validation rules. Baseline 3 is appropriate when the schema does the heavy lifting, but no extra value is provided.

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 tool's purpose: 'Validate export request parameters before execution to prevent errors.' It specifies the verb 'validate' and the resource 'export request parameters,' making it distinct from general validation tools. However, it doesn't explicitly differentiate from sibling tools like 'export_mailboxes_13490737e0' or 'export_guidance,' which could be related but serve different functions.

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 minimal guidance: it implies usage before executing an export to prevent errors, but doesn't specify when to use this tool versus alternatives (e.g., 'export_mailboxes_13490737e0' for actual export). No explicit when-not-to-use scenarios or prerequisites are mentioned, leaving the agent with vague context for tool selection.

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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