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gitlab_retry_pipeline

Retry failed GitLab pipelines to resume CI/CD workflows after errors. Specify project path and pipeline ID to restart execution.

Instructions

Retries a failed pipeline.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectPathYesThe path of the GitLab project.
pipelineIdYesThe ID of the pipeline to retry.

Implementation Reference

  • src/index.ts:718-735 (registration)
    Registration of the 'gitlab_retry_pipeline' tool, including its description and input schema definition.
    {
      name: 'gitlab_retry_pipeline',
      description: 'Retries a failed pipeline.',
      inputSchema: {
        type: 'object',
        properties: {
          projectPath: {
            type: 'string',
            description: 'The path of the GitLab project.',
          },
          pipelineId: {
            type: 'number',
            description: 'The ID of the pipeline to retry.',
          },
        },
        required: ['projectPath', 'pipelineId'],
      },
    },
  • The main handler for the gitlab_retry_pipeline tool within the CallToolRequest handler's switch statement. Extracts arguments and calls GitLabService.retryPipeline.
    case 'gitlab_retry_pipeline': {
      if (!gitlabService) {
        throw new Error('GitLab service is not initialized.');
      }
      const { projectPath, pipelineId } = args as { projectPath: string; pipelineId: number };
      const result = await gitlabService.retryPipeline(projectPath, pipelineId);
      return {
        content: [
          {
            type: 'text',
            text: `Pipeline retry triggered successfully: ${JSON.stringify(result, null, 2)}`,
          },
        ],
      };
    }
  • Helper method in GitLabService class that implements the core logic: POST request to GitLab API to retry the specified pipeline.
    async retryPipeline(projectPath: string, pipelineId: number): Promise<any> {
      const encodedProjectPath = encodeURIComponent(projectPath);
      return this.callGitLabApi<any>(
        `projects/${encodedProjectPath}/pipelines/${pipelineId}/retry`,
        'POST',
      );
    }
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. It states the action ('retries') but doesn't explain what 'retry' entails (e.g., re-running all jobs, resetting status, permissions required, side effects, or error handling). This is a significant gap for a mutation tool with zero annotation coverage.

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 waste. It's front-loaded with the core action and resource, making it easy to parse quickly without unnecessary elaboration.

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 complexity of a mutation tool (retrying a pipeline) with no annotations and no output schema, the description is incomplete. It lacks details on behavior, outcomes, error conditions, or how it differs from sibling tools, making it inadequate for safe and effective use by an AI agent.

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%, with clear descriptions for both parameters ('projectPath' and 'pipelineId'). The description adds no additional parameter semantics beyond what the schema provides, so 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 ('retries') and target resource ('a failed pipeline'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'gitlab_cancel_pipeline' or 'gitlab_trigger_pipeline' in terms of when to use each, which prevents a perfect 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. It doesn't mention prerequisites (e.g., that the pipeline must be in a failed state), contrast it with 'gitlab_cancel_pipeline' or 'gitlab_trigger_pipeline', or specify any constraints, leaving the agent to infer usage from the name 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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