google-workspace-mcp-server

Resolve Comment

drive_resolve_comment

Idempotent

Resolve a comment in Google Docs by supplying the file ID and comment ID to mark it as resolved.

Instructions

Mark a comment as resolved on a Google Doc.

Args:

file_id (string): The ID of the Google Doc
comment_id (string): The ID of the comment to resolve

Returns: { "id": string, "resolved": true }

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "file_id": "<file_id>",
      "comment_id": "<comment_id>"
    },
    "name": "drive_resolve_comment"
  }
}

Input Schema

Name	Required	Description	Default
`file_id`	Yes	The ID of the Google Doc containing the comment
`comment_id`	Yes	The ID of the comment to resolve

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.4.3May 26, 2026

TDQS

A3.8/5.0

Behavior3/5

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

Annotations already disclose readOnly=false, destructive=false, and idempotent=true. The description adds that the result sets resolved=true and returns the comment id, which is useful. However, it does not explain side effects (e.g., whether resolution is reversible, permissions needed) or error behavior. The extra context beyond annotations is present but minimal.

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 compact and well-structured: a one-sentence purpose, a clear Args list, and a Returns block. It is front-loaded and every element serves a purpose, with no fluff or redundant 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?

The tool is simple with only two required string parameters and no nested objects. The description provides the return shape, and annotations cover the mutation and idempotency profile. Missing details like error handling or permission requirements are minor and unlikely to mislead an agent for this basic operation.

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 both file_id and comment_id clearly described. The description repeats this information without adding new semantics such as formats, lifecycle constraints, or prerequisites. Therefore it adds no value beyond the structured schema, fitting the baseline 3.

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 opens with 'Mark a comment as resolved on a Google Doc', using a specific verb and resource. This clearly distinguishes it from sibling comment tools (list, create, reply, delete) and leaves no ambiguity about what it does.

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

Usage Guidelines3/5

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

The description implies when to use the tool (when you need to mark a comment resolved), but provides no explicit guidance on when not to use it or alternatives. Sibling tools like drive_delete_comment or drive_reply_to_comment are not mentioned, so the agent must infer the appropriate choice from context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.