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get_task_comments

Retrieve all comments for a specific ClickUp task, including author, text, and timestamps.

Instructions

Get comments for a ClickUp task. Returns comment details including text, author, and timestamps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_idYesThe ID of the task to get comments for
startNoPagination start (timestamp)
start_idNoPagination start ID

Implementation Reference

  • Registration of the 'get_task_comments' tool on the MCP server with Zod schema for task_id, start, and start_id parameters. The tool handler calls commentsClient.getTaskComments().
    export function setupCommentTools(server: McpServer): void {
      // Register get_task_comments tool
      server.tool(
        'get_task_comments',
        'Get comments for a ClickUp task. Returns comment details including text, author, and timestamps.',
        {
          task_id: z.string().describe('The ID of the task to get comments for'),
          start: z.number().optional().describe('Pagination start (timestamp)'),
          start_id: z.string().optional().describe('Pagination start ID')
        },
        async ({ task_id, ...params }) => {
          try {
            const result = await commentsClient.getTaskComments(task_id, params);
            return {
              content: [{ type: 'text', text: JSON.stringify(result, null, 2) }]
            };
          } catch (error: any) {
            console.error('Error getting task comments:', error);
            return {
              content: [{ type: 'text', text: `Error getting task comments: ${error.message}` }],
              isError: true
            };
          }
        }
      );
  • Handler function for the 'get_task_comments' tool. Takes task_id and optional pagination params (start, start_id), calls the comments client, and returns the result as JSON text.
    async ({ task_id, ...params }) => {
      try {
        const result = await commentsClient.getTaskComments(task_id, params);
        return {
          content: [{ type: 'text', text: JSON.stringify(result, null, 2) }]
        };
      } catch (error: any) {
        console.error('Error getting task comments:', error);
        return {
          content: [{ type: 'text', text: `Error getting task comments: ${error.message}` }],
          isError: true
        };
      }
    }
  • Zod schema defining input parameters for get_task_comments: task_id (required string), start (optional number), start_id (optional string).
    {
      task_id: z.string().describe('The ID of the task to get comments for'),
      start: z.number().optional().describe('Pagination start (timestamp)'),
      start_id: z.string().optional().describe('Pagination start ID')
    },
  • The getTaskComments method on CommentsClient. Makes a GET request to /task/{taskId}/comment with optional query parameters. Returns a promise of comments array.
    async getTaskComments(taskId: string, params?: GetTaskCommentsParams): Promise<{ comments: Comment[] }> {
      return this.client.get(`/task/${taskId}/comment`, params);
    }
  • GetTaskCommentsParams interface defining optional start (number) and start_id (string) properties for pagination.
    export interface GetTaskCommentsParams {
      start?: number;
      start_id?: string;
    }
Behavior2/5

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

No annotations are provided, so the description must carry full behavioral disclosure. It mentions return content but does not discuss pagination behavior (despite pagination parameters), ordering, or what happens when a task has no comments. The tool's read-only nature is implied but not explicit.

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 concise with two sentences, front-loaded with the main action, and contains no redundant information. Every word contributes to understanding.

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

Completeness3/5

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

Given the low complexity and high schema coverage, the description is fairly complete but could improve by explaining pagination (using start/start_id) or confirming the read-only nature. The absence of an output schema is partially mitigated by mentioning return details.

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

Parameters4/5

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

The input schema has 100% parameter description coverage. The description adds value by outlining the return structure (text, author, timestamps), which complements the schema. However, it does not elaborate on the purpose of 'start' and 'start_id' beyond their schema descriptions.

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 clearly states the tool's purpose: 'Get comments for a ClickUp task' with specific return details (text, author, timestamps). It distinguishes itself from sibling tools like create_task_comment or get_list_comments.

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 usage context (get comments for a task) but provides no explicit guidance on when to use this tool versus alternatives like get_threaded_comments or get_chat_view_comments. No exclusions or prerequisites are mentioned.

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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