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aliyun

AlibabaCloud DevOps MCP Server

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by aliyun

create_estimated_effort

Register estimated work hours for Alibaba Cloud DevOps project tasks to track time allocation and improve project planning accuracy.

Instructions

[Project Management] 登记预计工时

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes工作项唯一标识
organizationIdYesorganizationId
descriptionNo工作描述
operatorIdNo操作者的useId,个人token时该参数无效
ownerYes负责人,填userId
spentTimeYes预计工时
workTypeNo工作类别

Implementation Reference

  • MCP tool handler case for 'create_estimated_effort': parses input with CreateEstimatedEffortSchema and delegates to effort.createEstimatedEffort
    case "create_estimated_effort": {
      const args = types.CreateEstimatedEffortSchema.parse(request.params.arguments);
      const result = await effort.createEstimatedEffort({
        id: args.id,
        organizationId: args.organizationId,
        description: args.description,
        operatorId: args.operatorId,
        owner: args.owner,
        spentTime: args.spentTime,
        workType: args.workType
      });
      return {
        content: [{ type: "text", text: JSON.stringify(result, null, 2) }],
      };
    }
  • Registration of the 'create_estimated_effort' tool in the getEffortTools array, including name, description, and zodToJsonSchema input schema.
    {
      name: "create_estimated_effort",
      description: "[Project Management] 登记预计工时",
      inputSchema: zodToJsonSchema(CreateEstimatedEffortSchema),
    },
  • Business logic implementation: validates parameters with CreateEstimatedEffortRequestSchema, constructs API URL, and performs POST request to create estimated effort record.
    export async function createEstimatedEffort(
      params: z.infer<typeof CreateEstimatedEffortRequestSchema> & {
        id: string;
        organizationId: string;
      }
    ) {
      const validatedParams = CreateEstimatedEffortRequestSchema.parse({
        description: params.description,
        operatorId: params.operatorId,
        owner: params.owner,
        spentTime: params.spentTime,
        workType: params.workType
      });
      
      const url = `/oapi/v1/projex/organizations/${params.organizationId}/workitems/${params.id}/estimatedEfforts`;
      
      const response = await yunxiaoRequest(url, {
        method: "POST",
        body: validatedParams
      });
    
      return IdentifierDTOSchema.parse(response);
    }
  • Zod schema defining the input parameters for the create_estimated_effort tool (re-exported via common/types.ts).
    export const CreateEstimatedEffortSchema = z.object({
      id: z.string().describe("工作项唯一标识"),
      organizationId: z.string().describe("organizationId"),
      description: z.string().max(500).optional().describe("工作描述"),
      operatorId: z.string().optional().describe("操作者的useId,个人token时该参数无效"),
      owner: z.string().describe("负责人,填userId"),
      spentTime: z.number().positive().describe("预计工时"),
      workType: z.string().optional().describe("工作类别"),
    });
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While '登记' implies a write/create operation, the description doesn't mention permissions required, whether the operation is idempotent, what happens on duplicate attempts, or what the response contains. For a 7-parameter mutation tool with zero annotation coverage, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise - just two Chinese characters for the core function plus a bracketed context label. While efficient, the bracketed '[Project Management]' adds minimal value and could be integrated more naturally. The description gets straight to the point with zero waste.

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 7-parameter mutation tool with no annotations and no output schema, the description is inadequate. It doesn't explain what happens after creation, what the return value contains, error conditions, or how this differs from related tools. The description should provide more context given the tool's complexity and lack of structured metadata.

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 description coverage is 100%, so the schema already documents all 7 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. The baseline score of 3 is appropriate when the schema does the heavy lifting for parameter documentation.

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 ('登记' which translates to 'register' or 'record') and the resource ('预计工时' meaning 'estimated effort'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'create_effort_record' or 'update_estimated_effort', which appear to be related operations.

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. There are no mentions of prerequisites, when-not-to-use scenarios, or comparisons to sibling tools like 'create_effort_record' or 'update_estimated_effort' that appear to handle similar resources.

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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