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jootsuki

Backlog MCP Server

by jootsuki

getIssue

Retrieve specific Backlog issues by ID to access project details, status, and task information for tracking and management.

Instructions

特定のBacklog課題を取得します

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issueIdYes課題のID(例: PROJECT-1)

Implementation Reference

  • MCP CallToolRequest handler for 'getIssue': validates input arguments using getIssueSchema, calls BacklogClient.getIssue, and returns the result as JSON text content.
    case 'getIssue': {
      const args = this.validateAndCastArguments<GetIssueArgs>(
        request.params.arguments,
        getIssueSchema
      );
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify(
              await this.backlogClient.getIssue(args),
              null,
              2
            ),
          },
        ],
      };
    }
  • Core implementation of getIssue: makes HTTP GET request to Backlog API endpoint /issues/{issueId} using axios and returns the issue data.
    async getIssue(args: GetIssueArgs): Promise<BacklogIssue> {
      try {
        const response = await this.client.get(`/issues/${args.issueId}`);
        return response.data;
      } catch (error) {
        if (axios.isAxiosError(error)) {
          throw new Error(`Backlog API error: ${error.response?.data.message ?? error.message}`);
        }
        throw error;
      }
    }
  • src/index.ts:95-98 (registration)
    Tool registration in ListTools response: defines name, description, and input schema for the 'getIssue' tool.
      name: 'getIssue',
      description: '特定のBacklog課題を取得します',
      inputSchema: getIssueSchema,
    },
  • Input schema definition for getIssue tool: requires 'issueId' as string.
    export const getIssueSchema = {
      type: 'object',
      properties: {
        issueId: {
          type: 'string',
          description: '課題のID(例: PROJECT-1)',
        },
      },
      required: ['issueId'],
    } as const;
  • TypeScript interface for GetIssueArgs used in handler and client.
    export interface GetIssueArgs {
      issueId: string;
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves a specific issue but doesn't mention whether this is a read-only operation, what permissions are required, how errors are handled (e.g., invalid issue IDs), or the format of the return data. For a retrieval tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 front-loaded with the core action and resource, making it easy to parse. Every part of the sentence contributes to understanding the tool's 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 the lack of annotations and output schema, the description is incomplete for a tool that retrieves data. It doesn't explain what information is returned (e.g., issue details, status, comments) or how to interpret the output. For a retrieval tool with no structured output documentation, this leaves the agent guessing about the result format and usability.

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 the 'issueId' parameter clearly documented as the issue ID (e.g., 'PROJECT-1'). The description doesn't add any additional meaning beyond this, such as explaining ID formats or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the 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 action ('取得します' - get/retrieve) and resource ('特定のBacklog課題' - specific Backlog issue), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'searchIssues' (which likely searches multiple issues) or 'getProjects' (which retrieves projects rather than issues), so it doesn't reach the highest score.

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 like 'searchIssues' or 'updateIssue'. It doesn't mention prerequisites, such as needing a valid issue ID, or contextual factors like whether this is for single-issue retrieval versus bulk operations. The agent must infer usage from the tool name and description alone.

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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