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gitlab_get_issue_details

Retrieve detailed information about a specific GitLab issue by providing the project path and issue internal ID. This tool enables AI agents to access issue data for integration workflows.

Instructions

Gets detailed information about a specific GitLab issue.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectPathYesThe path of the GitLab project.
issueIidYesThe internal ID of the issue.

Implementation Reference

  • The core handler function in GitLabService that fetches detailed information about a GitLab issue using the GitLab API endpoint.
    async getIssueDetails(projectPath: string, issueIid: number): Promise<any> {
      const encodedProjectPath = encodeURIComponent(projectPath);
      return this.callGitLabApi<any>(
        `projects/${encodedProjectPath}/issues/${issueIid}`,
      );
    }
  • Input schema definition for the gitlab_get_issue_details tool, specifying parameters projectPath and issueIid.
      name: 'gitlab_get_issue_details',
      description: 'Gets detailed information about a specific GitLab issue.',
      inputSchema: {
        type: 'object',
        properties: {
          projectPath: {
            type: 'string',
            description: 'The path of the GitLab project.',
          },
          issueIid: {
            type: 'number',
            description: 'The internal ID of the issue.',
          },
        },
        required: ['projectPath', 'issueIid'],
      },
    },
  • src/index.ts:1970-1983 (registration)
    Tool registration in the MCP server request handler switch statement, dispatching calls to gitlabService.getIssueDetails and formatting the response.
    case 'gitlab_get_issue_details': {
      if (!gitlabService) {
        throw new Error('GitLab service is not initialized.');
      }
      const { projectPath, issueIid } = args as { projectPath: string; issueIid: number };
      const result = await gitlabService.getIssueDetails(projectPath, issueIid);
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify(result, null, 2),
          },
        ],
      };
  • src/index.ts:848-864 (registration)
    Tool object registration in the allTools array, which is used for listTools and filtered for availability.
      name: 'gitlab_get_issue_details',
      description: 'Gets detailed information about a specific GitLab issue.',
      inputSchema: {
        type: 'object',
        properties: {
          projectPath: {
            type: 'string',
            description: 'The path of the GitLab project.',
          },
          issueIid: {
            type: 'number',
            description: 'The internal ID of the issue.',
          },
        },
        required: ['projectPath', 'issueIid'],
      },
    },
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 'Gets detailed information' but doesn't clarify what 'detailed' includes (e.g., fields like labels, assignees, or description), whether it's a read-only operation, authentication requirements, rate limits, or error handling. This leaves significant gaps for a tool that likely interacts with an external API.

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 with zero wasted words. It front-loads the core purpose ('Gets detailed information') and specifies the resource, making it easy to parse. Every part of the sentence contributes directly 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 with external API interactions. It doesn't cover behavioral aspects like read-only nature, return format, error cases, or authentication needs. While the schema handles parameters well, the overall context for safe and effective use is insufficient.

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?

Schema description coverage is 100%, with clear parameter descriptions in the schema (e.g., 'The path of the GitLab project' for projectPath). The description adds no additional meaning beyond implying specificity ('about a specific GitLab issue'), which aligns with the schema but doesn't enhance it. This meets the baseline for high schema coverage.

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 ('Gets') and resource ('detailed information about a specific GitLab issue'), making the purpose unambiguous. It distinguishes from siblings like gitlab_list_project_issues (which lists issues) and gitlab_get_issue_comments (which focuses on comments). However, it doesn't explicitly contrast with all siblings, such as gitlab_get_merge_request_details, which follows a similar pattern for a different resource.

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. It doesn't mention prerequisites (e.g., needing project access), contrast with gitlab_list_project_issues for browsing issues, or specify scenarios like retrieving issue metadata for updates. Usage is implied by the name but not explicitly stated.

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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