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create_label

Create a new Gmail label. Labels can be used to organize emails. After creation, use add_labels to apply the label to messages.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesName for the new label (e.g., 'Projects/Alpha' for nested labels)
labelListVisibilityNoWhether to show the label in the label list: labelShow (default), labelShowIfUnread, or labelHide
messageListVisibilityNoWhether to show the label in the message list: show (default) or hide

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
nameYes
typeNo
messageYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / additionalProperties
      Removed value: -false
  2. Added

TDQS

A3.8/5.0
Behavior3/5

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

Annotations indicate this is a non-destructive write operation (readOnlyHint: false, destructiveHint: false), which the description aligns with by stating 'Create a new Gmail label'. The description adds context about post-creation usage with 'add_labels', but doesn't disclose additional behavioral traits like permissions, rate limits, or error handling beyond what annotations provide.

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 two sentences, front-loaded with the core action, and every sentence adds value: the first defines the tool's purpose, and the second provides practical guidance on next steps. There is no wasted text.

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?

Given the tool's moderate complexity, rich schema with 100% coverage, annotations, and an output schema (implied by context signals), the description is mostly complete. It covers purpose and usage flow but lacks details on output or error cases, though the output schema mitigates this gap.

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%, with detailed descriptions for all parameters including enums and defaults. The description doesn't add any parameter-specific information beyond the schema, so it meets the baseline of 3 without compensating for gaps, as there are none.

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 action ('Create a new Gmail label') and resource ('Gmail label'), distinguishing it from siblings like 'add_labels' or 'delete_label'. However, it doesn't explicitly differentiate from 'list_labels' in terms of creation vs. listing, though the verb 'create' makes the purpose evident.

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 by mentioning that labels organize emails and suggesting 'add_labels' for applying them after creation. It implies usage for label creation but doesn't explicitly state when not to use it or compare to alternatives like 'delete_label' or 'list_labels'.

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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