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suspendWorkflow

Pause a running workflow instance in Adobe Experience Manager to temporarily halt automated processes for maintenance or issue resolution.

Instructions

Suspend a workflow instance

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workflowIdYes
reasonNo

Implementation Reference

  • Core handler implementation that performs HTTP POST to AEM's /etc/workflow/instances/{workflowId} endpoint with action 'suspend' to suspend the workflow.
    async suspendWorkflow(workflowId: string, reason?: string): Promise<{
      success: boolean;
      operation: string;
      timestamp: string;
      data: {
        workflowId: string;
        reason?: string;
        status: string;
        suspendedAt: string;
      };
    }> {
      return safeExecute(async () => {
        if (!workflowId) {
          throw createAEMError(
            AEM_ERROR_CODES.INVALID_PARAMETERS, 
            'Workflow ID is required', 
            { workflowId }
          );
        }
    
        // Suspend the workflow
        const suspendData = {
          action: 'suspend',
          reason: reason || 'Suspended via AEM MCP Server'
        };
    
        const response = await this.httpClient.post(
          `/etc/workflow/instances/${workflowId}`, 
          suspendData,
          {
            headers: {
              'Content-Type': 'application/json'
            }
          }
        );
    
        return createSuccessResponse({
          workflowId,
          reason: suspendData.reason,
          status: 'SUSPENDED',
          suspendedAt: new Date().toISOString()
        }, 'suspendWorkflow');
      }, 'suspendWorkflow');
    }
  • MCP server CallToolRequestSchema handler that extracts parameters from MCP request and delegates to AEMConnector.suspendWorkflow
    case 'suspendWorkflow': {
      const { workflowId, reason } = args as { workflowId: string; reason?: string };
      const result = await aemConnector.suspendWorkflow(workflowId, reason);
      return { content: [{ type: 'text', text: JSON.stringify(result, null, 2) }] };
    }
  • Input schema definition for the suspendWorkflow tool used in MCP listTools response
    {
      name: 'suspendWorkflow',
      description: 'Suspend a workflow instance',
      inputSchema: {
        type: 'object',
        properties: {
          workflowId: { type: 'string' },
          reason: { type: 'string' }
        },
        required: ['workflowId'],
      },
    },
  • Custom MCPRequestHandler switch case that handles suspendWorkflow requests and calls AEMConnector
    case 'suspendWorkflow':
      return await this.aemConnector.suspendWorkflow(params.workflowId, params.reason);
  • AEMConnector wrapper method that delegates suspendWorkflow call to WorkflowOperations module
    async suspendWorkflow(workflowId: string, reason?: string) {
      return this.workflowOps.suspendWorkflow(workflowId, reason);
    }
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 implies a mutation action ('suspend') but doesn't specify permissions needed, side effects, reversibility, or response format. This leaves critical behavioral traits undocumented for a tool that likely alters system state.

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 no wasted words, making it highly concise and front-loaded. Every part of the sentence contributes directly to stating the tool's purpose.

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 workflow suspension tool with no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on behavior, parameters, and expected outcomes, 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.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, so parameters 'workflowId' and 'reason' are undocumented. The description adds no semantic information about these parameters, such as what 'workflowId' refers to or how 'reason' is used, failing to compensate for the schema gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Suspend a workflow instance' clearly states the action (suspend) and target (workflow instance), which is better than a tautology. However, it doesn't distinguish this tool from sibling tools like 'cancelWorkflow', 'resumeWorkflow', or 'completeWorkflowStep', leaving the specific purpose vague relative to alternatives.

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 such as 'cancelWorkflow' or 'resumeWorkflow'. It lacks context about prerequisites, appropriate scenarios, or exclusions, offering only a basic statement of function without usage instructions.

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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