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Waroom MCP

by topotal

waroom_create_service_label

Create new labels for services in Waroom to organize and categorize incident management data with custom names and colors.

Instructions

特定のサービスに新しいラベルを作成します。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
service_nameYesサービス名
nameYesラベル名
colorYesラベルの色(6桁の16進数カラーコード、例: ff0000)

Implementation Reference

  • The MCP tool handler function that calls WaroomClient.createServiceLabel with the input parameters and returns the JSON response or an error message as text content.
    async (params) => {
      try {
        const response = await waroomClient.createServiceLabel(
          params.service_name,
          params.name,
          params.color
        );
        return {
          content: [{
            type: 'text',
            text: JSON.stringify(response, null, 2)
          }]
        };
      } catch (error) {
        return {
          content: [{
            type: 'text',
            text: `サービスラベルの作成に失敗しました: ${error}`
          }]
        };
      }
    }
  • Zod schema defining the input parameters for the tool: service_name (string), name (string), color (6-digit hex string).
    {
      service_name: z.string().min(1).max(100).describe('サービス名'),
      name: z.string().min(1).max(100).describe('ラベル名'),
      color: z.string().regex(/^[0-9a-fA-F]{6}$/).describe('ラベルの色(6桁の16進数カラーコード、例: ff0000)'),
    },
  • Direct registration of the 'waroom_create_service_label' tool to the MCP server using server.tool(), specifying name, description, input schema, and handler function.
    server.tool(
      'waroom_create_service_label',
      '特定のサービスに新しいラベルを作成します。',
      {
        service_name: z.string().min(1).max(100).describe('サービス名'),
        name: z.string().min(1).max(100).describe('ラベル名'),
        color: z.string().regex(/^[0-9a-fA-F]{6}$/).describe('ラベルの色(6桁の16進数カラーコード、例: ff0000)'),
      },
      async (params) => {
        try {
          const response = await waroomClient.createServiceLabel(
            params.service_name,
            params.name,
            params.color
          );
          return {
            content: [{
              type: 'text',
              text: JSON.stringify(response, null, 2)
            }]
          };
        } catch (error) {
          return {
            content: [{
              type: 'text',
              text: `サービスラベルの作成に失敗しました: ${error}`
            }]
          };
        }
      }
    );
  • Supporting method in WaroomClient that performs the actual HTTP POST request to the Waroom API to create a service label.
    async createServiceLabel(serviceName: string, name: string, color: string) {
      try {
        const response = await this.axiosInstance.post(`${this.baseUrl}/services/${serviceName}/labels`, {
          label: {
            name,
            color
          }
        });
        return response.data;
      } catch (error) {
        throw new Error(`Failed to create service label: ${error}`);
      }
    }
  • src/main.ts:29-29 (registration)
    Top-level call to createLabelsTools(server, waroomClient) which registers all label-related tools, including 'waroom_create_service_label'.
    createLabelsTools(server, waroomClient);
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 'creates' implies a write/mutation operation, the description doesn't disclose important behavioral traits like: what permissions are required, whether this operation is idempotent, what happens if a label with the same name already exists, what the response format looks like, or any rate limits. The description is minimal and lacks necessary context for safe invocation.

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 Japanese that directly states the tool's purpose without unnecessary words. It's appropriately sized for what it communicates, though what it communicates is limited. Every word earns its place in conveying the basic function.

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?

Given that this is a mutation tool (creates new resources) with no annotations and no output schema, the description is insufficiently complete. It doesn't address important contextual aspects like: what happens after creation (is the label immediately available?), error conditions, authentication requirements, or how this tool relates to the broader service label management workflow. The description provides only the most basic functional statement without necessary operational context.

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 input schema has 100% description coverage with clear parameter documentation in Japanese. The description doesn't add any meaningful parameter semantics beyond what's already in the schema - it doesn't explain relationships between parameters, provide examples of valid service_name values, or clarify the purpose of the color parameter beyond the schema's pattern constraint. With complete schema coverage, the baseline score of 3 is appropriate.

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 ('新しいラベルを作成します' - creates a new label) and the target resource ('特定のサービスに' - for a specific service), which is a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'waroom_update_service_label' or explain how it differs from 'waroom_create_incident' or other creation tools in the system.

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 multiple sibling tools for creating different resources (incidents, postmortems, metrics) and for managing service labels (get, update, delete), but the description doesn't indicate when label creation is appropriate versus other operations or what prerequisites might exist.

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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