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Tencent Cloud COS MCP Server

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by Tencent

describeDocProcessJob

Retrieve the status and results of a specific document transcoding task using its job ID. Enables easy tracking and management of document processing operations on Tencent Cloud COS MCP Server.

Instructions

根据 jobid 查询指定的文档转码任务结果

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdYes要查询的任务ID,可通过提交文档任务的响应中获取。

Implementation Reference

  • Core handler function implementing the logic to query Tencent Cloud COS for the document processing job status using the provided jobId.
    async describeDocProcessJob(jobId: string) {
      try {
        let host = this.bucket + '.ci.' + this.region + '.myqcloud.com';
        let url = 'https://' + host + '/doc_jobs/' + jobId;
        const result = await new Promise((resolve, reject) => {
          this.cos.request(
            {
              Bucket: this.bucket, // Bucket 格式:test-1250000000
              Region: this.region,
              Method: 'GET',
              Key: 'doc_jobs/' + jobId,
              Url: url,
            },
            function (error, data) {
              if (error) {
                // 处理请求失败
                reject(error);
              } else {
                // 处理请求成功
                resolve(data);
                //获取返回的jobid, 去调查询任务接口, 返回具体信息
              }
            },
          );
        });
    
        return {
          isSuccess: true,
          message: '文档转pdf成功',
          data: result,
        };
      } catch (error) {
        return {
          isSuccess: false,
          message: '文档转pdf失败',
          data: error,
        };
      }
    }
  • src/server.ts:551-571 (registration)
    MCP server tool registration, defining the tool name, description, input schema (jobId as string), and handler that delegates to the service instance.
    server.tool(
      'describeDocProcessJob',
      '根据 jobid 查询指定的文档转码任务结果',
      {
        jobId: z
          .string()
          .describe('要查询的任务ID,可通过提交文档任务的响应中获取。'),
      },
      async ({ jobId }) => {
        const res = await CIDocInstance.describeDocProcessJob(jobId);
        return {
          content: [
            {
              type: 'text',
              text: JSON.stringify(res.data, null, 2),
            },
          ],
          isError: !res.isSuccess,
        };
      },
    );
  • Zod input schema validation for the jobId parameter.
      jobId: z
        .string()
        .describe('要查询的任务ID,可通过提交文档任务的响应中获取。'),
    },
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only states the query action without mentioning whether this is a read-only operation, what permissions might be required, what happens if the job ID doesn't exist, or what format the results will be in. For a query tool with zero annotation coverage, this leaves significant behavioral gaps.

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 in Chinese that directly states the tool's purpose without any unnecessary words or elaboration. Every word serves a clear purpose in conveying the core functionality.

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 query tool with no annotations and no output schema, the description is insufficient. It doesn't explain what information the query returns (status, progress, output location, error details), what happens for invalid/nonexistent job IDs, or any rate limits or authentication requirements. The context signals indicate this is a simple tool, but the description leaves too many operational questions unanswered.

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 schema has 100% description coverage, with the single parameter 'jobId' well-documented in the schema itself. The description adds minimal value beyond what's already in the schema - it mentions job IDs come from document task submissions, but this is essentially restating the schema's description. Baseline 3 is appropriate when schema does the heavy lifting.

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 verb ('查询' - query) and resource ('文档转码任务结果' - document transcoding job result), specifying what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'describeMediaJob' which might have similar query functionality for different resource types.

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 no guidance on when to use this tool versus alternatives. While it mentions job IDs come from '提交文档任务的响应' (responses from submitting document tasks), it doesn't specify when to query versus when to use other tools like 'createDocToPdfJob' or how this differs from 'describeMediaJob' for media-related queries.

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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