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patch_label

Modify Gmail label properties like name, visibility, or color using partial updates to customize email organization.

Instructions

Patch an existing label (partial update)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe ID of the label to patch
nameNoThe display name of the label
messageListVisibilityNoThe visibility of messages with this label in the message list
labelListVisibilityNoThe visibility of the label in the label list
colorNoThe color settings for the label

Implementation Reference

  • Handler function for 'patch_label' tool: destructures params to get id and labelData, calls Gmail API labels.patch via handleTool wrapper, formats response.
    async (params) => {
      const { id, ...labelData } = params
      return handleTool(config, async (gmail: gmail_v1.Gmail) => {
        const { data } = await gmail.users.labels.patch({ userId: 'me', id, requestBody: labelData })
        return formatResponse(data)
      })
    }
  • Input schema for 'patch_label' tool using Zod: defines id (required), and optional fields for name, visibilities, and color object.
      id: z.string().describe("The ID of the label to patch"),
      name: z.string().optional().describe("The display name of the label"),
      messageListVisibility: z.enum(['show', 'hide']).optional().describe("The visibility of messages with this label in the message list"),
      labelListVisibility: z.enum(['labelShow', 'labelShowIfUnread', 'labelHide']).optional().describe("The visibility of the label in the label list"),
      color: z.object({
        textColor: z.string().describe("The text color of the label as hex string"),
        backgroundColor: z.string().describe("The background color of the label as hex string")
      }).optional().describe("The color settings for the label")
    },
  • src/index.ts:478-497 (registration)
    Registration of 'patch_label' tool on McpServer: includes name, description, input schema, and inline handler function.
    server.tool("patch_label",
      "Patch an existing label (partial update)",
      {
        id: z.string().describe("The ID of the label to patch"),
        name: z.string().optional().describe("The display name of the label"),
        messageListVisibility: z.enum(['show', 'hide']).optional().describe("The visibility of messages with this label in the message list"),
        labelListVisibility: z.enum(['labelShow', 'labelShowIfUnread', 'labelHide']).optional().describe("The visibility of the label in the label list"),
        color: z.object({
          textColor: z.string().describe("The text color of the label as hex string"),
          backgroundColor: z.string().describe("The background color of the label as hex string")
        }).optional().describe("The color settings for the label")
      },
      async (params) => {
        const { id, ...labelData } = params
        return handleTool(config, async (gmail: gmail_v1.Gmail) => {
          const { data } = await gmail.users.labels.patch({ userId: 'me', id, requestBody: labelData })
          return formatResponse(data)
        })
      }
    )
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states 'patch' implies mutation but doesn't disclose permissions needed, whether changes are reversible, rate limits, or what happens to unspecified fields. 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 with zero waste. It's front-loaded with the core action and resource, making it easy to parse quickly.

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 no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like permissions, side effects, or response format, leaving significant gaps for an AI agent to understand tool usage.

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 the schema fully documents all 5 parameters. The description adds no additional parameter semantics beyond what's in the schema, such as format examples or constraints. Baseline 3 is appropriate when schema does all the work.

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 ('patch') and resource ('existing label'), with 'partial update' specifying the type of modification. It distinguishes from 'update_label' (likely a full update) by mentioning partial updates, though not explicitly contrasting with sibling tools.

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?

No guidance is provided on when to use this tool versus alternatives like 'update_label' (a sibling tool). The description implies partial updates but doesn't specify prerequisites, error conditions, or when to choose this over other label-related tools.

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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