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get_render_queue

Check current render queue status and items in Adobe Premiere Pro projects to monitor export progress and manage video processing tasks.

Instructions

Get current render queue status and items

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function that fetches the current render queue status from the Premiere Pro HTTP API endpoint, processes the data to format queue items with status emojis, progress, and estimated time, handles empty queue and errors, and returns a structured MCP response.
    async getRenderQueue() {
      try {
        const response = await fetch('http://localhost:3001/api/render-queue');
        if (!response.ok) throw new Error(`HTTP ${response.status}: ${response.statusText}`);
        
        const data = await response.json();
        
        if (data.error) {
          return {
            content: [
              {
                type: 'text',
                text: `⚠️  ${data.error}`,
              },
            ],
          };
        }
    
        if (data.total_queue_items === 0) {
          return {
            content: [
              {
                type: 'text',
                text: `🎬 **Render Queue**\n\nNo items in render queue.`,
              },
            ],
          };
        }
    
        const queueList = data.queue_items.map(item => {
          const statusEmoji = {
            'queued': '⏳',
            'rendering': 'πŸ”„',
            'complete': 'βœ…',
            'error': '❌'
          }[item.status] || '❓';
          
          return `${statusEmoji} **${item.sequence_name}**\n  πŸ“ ${item.output_path}\n  βš™οΈ ${item.preset} | Progress: ${item.progress_percentage}%\n  ⏱️ ETA: ${item.estimated_time_remaining}`;
        }).join('\n\n');
    
        return {
          content: [
            {
              type: 'text',
              text: `🎬 **Render Queue (${data.total_queue_items} items)**\n\n${queueList}`,
            },
          ],
        };
      } catch (error) {
        return {
          content: [
            {
              type: 'text',
              text: `❌ **Failed to get render queue**\n\nError: ${error.message}`,
            },
          ],
          isError: true,
        };
      }
    }
  • The input schema for the get_render_queue tool, defining it as an object with no properties or required parameters.
    inputSchema: {
      type: "object",
      properties: {},
      required: []
  • mcp-server.js:137-145 (registration)
    Registration of the get_render_queue tool in the ListToolsRequestSchema response, including name, description, and input schema.
    {
      name: "get_render_queue",
      description: "Get current render queue status and items",
      inputSchema: {
        type: "object",
        properties: {},
        required: []
      }
    },
  • mcp-server.js:255-256 (registration)
    Registration/dispatch logic in the CallToolRequestSchema handler's switch statement that routes calls to the getRenderQueue handler.
    case 'get_render_queue':
      return await this.getRenderQueue();
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 'current render queue status and items,' implying a read-only operation, but doesn't specify if it requires authentication, has rate limits, returns real-time or cached data, or what format the output takes (e.g., list of items with statuses). For a 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 that front-loads the core purpose ('Get current render queue status and items') with zero wasted words. It's appropriately sized for a simple, parameter-less tool and earns its place by clearly stating the action and target resource.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally completeβ€”it tells the agent what the tool does. However, it lacks details on output format (e.g., whether it returns a list, object, or status codes) and behavioral context (e.g., permissions needed), which could be helpful despite the low complexity. It's adequate but leaves room for improvement in guiding the agent on what to expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

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

The tool has 0 parameters, and the schema description coverage is 100% (as there are no parameters to describe). The description doesn't need to add parameter semantics, so it meets the baseline of 4 for tools with no parameters, as it doesn't introduce confusion or redundancy.

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 tool's purpose with a specific verb ('Get') and resource ('render queue status and items'), making it immediately understandable. It distinguishes itself from siblings by focusing on render queue status rather than sequences, projects, or clips. However, it doesn't explicitly differentiate from all siblings (e.g., 'get_active_sequence_info' might also relate to rendering), so it falls short of a perfect 5.

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 an active project), exclusions, or comparisons to sibling tools like 'get_active_sequence_info' or 'get_sequence_details' that might overlap with rendering contexts. Without any usage context, the agent must infer when this tool is appropriate.

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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