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tosea_render_slides

Queue slide rendering for presentations, supporting all slides or specific slide numbers to generate visual content from documents.

Instructions

Queue slide rendering for all slides or a subset of slide numbers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
presentation_idYes
render_providerNo
forceNo
slides_to_generateNo

Implementation Reference

  • Registration and implementation handler for the 'tosea_render_slides' MCP tool.
    server.tool(
      "tosea_render_slides",
      "Queue slide rendering for all slides or a subset of slide numbers.",
      {
        presentation_id: z.string().uuid(),
        render_provider: z.string().optional(),
        force: z.boolean().default(false),
        slides_to_generate: z.array(z.number().int().min(1)).max(50).optional()
      },
      async ({ presentation_id, render_provider, force, slides_to_generate }) => {
        try {
          return asToolResult(
            await client.renderSlides({
              presentationId: presentation_id,
              renderProvider: render_provider,
              force,
              slidesToGenerate: normalizeSlideNumbers(slides_to_generate)
            })
          );
        } catch (error) {
          throw wrapToolError(error);
        }
      }
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 mentions 'Queue slide rendering,' implying an asynchronous operation that might involve background processing, but fails to detail critical aspects like authentication needs, rate limits, error handling, job status tracking, or what 'force' parameter does. This leaves significant gaps for a tool that likely triggers resource-intensive operations.

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 action ('Queue slide rendering') and scope ('for all slides or a subset'). There is no wasted verbiage or redundant information, making it highly concise and well-structured.

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 queuing operation with 4 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, parameter meanings, expected outputs, error conditions, and integration with sibling tools like 'tosea_wait_for_job.' This makes 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?

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It only vaguely references 'all slides or a subset of slide numbers,' which partially relates to 'slides_to_generate,' but doesn't explain the purpose of 'presentation_id,' 'render_provider,' or 'force.' This adds minimal value beyond the schema, failing to adequately clarify parameter meanings.

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 ('Queue slide rendering') and target ('for all slides or a subset of slide numbers'), providing a specific verb+resource combination. However, it doesn't explicitly distinguish this tool from sibling tools like 'tosea_export_presentation' or 'tosea_redownload_export', which might also involve presentation output generation, so it misses full sibling differentiation.

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, timing considerations, or how it relates to sibling tools like 'tosea_wait_for_job' (which might be needed after queuing) or 'tosea_export_presentation' (which might handle different output types).

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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