ppt-mcp

ppt_set_route_options

Define scanned-page mode, footer removal, and AI OCR model decisions to route the PDF-to-PPT conversion workflow.

Instructions

Write scanned-page, footer, and AI model decisions into the workflow.

This is step 3 of the high-level guided flow. Use ppt_list_route_models first when the user wants to select a non-default AI OCR model. Do not use this tool before pdf_path and page range are confirmed.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "route_workflow_id": "<route_workflow_id>"
    },
    "name": "ppt_set_route_options"
  }
}

Input Schema

Name	Required	Description	Default
`ocr_ai_model`	No
`route_workflow_id`	Yes
`scanned_page_mode`	No
`ocr_ai_model_decision`	No
`remove_footer_notebooklm`	No
`ocr_ai_model_choice_index`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 2, 2026

TDQS

A4.1/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses a sequencing precondition (step 3) and a prerequisite (pdf_path/page range confirmation), but does not describe side effects such as whether prior options are overwritten, whether the operation is idempotent, or what happens on failure. This is partially transparent but lacks mutation details.

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 only three sentences, front-loaded with the core purpose (Write decisions into workflow) followed by usage context and a clear warning. Every sentence adds value with no filler or redundancy.

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 6 parameters, 0% schema coverage, and no annotations, the description provides helpful guided-flow context (step 3) and a key precondition, but does not fully equip the agent to correctly set all parameters. The output schema exists but only specifies types/enums, not semantic relationships. It is adequate for a step in a flow but could elaborate on parameter decisions.

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 coverage is 0% and no parameter descriptions exist in the schema. The description maps high-level concepts ('scanned-page', 'footer', 'AI model') to parameter groups, which helps infer meaning for scanned_page_mode, remove_footer_notebooklm, and the OCR model fields. However, it does not explain individual parameters like route_workflow_id, ocr_ai_model_decision, or ocr_ai_model_choice_index, leaving gaps.

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

Purpose5/5

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

The description uses a specific verb 'Write' and identifies the resource (scanned-page, footer, and AI model decisions) and the destination (the workflow). It also distinguishes itself from the sibling tool ppt_list_route_models by referencing it as an alternative, clarifying its role as a setter rather than a lister.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use ppt_list_route_models first (when user wants a non-default AI OCR model) and when NOT to use this tool (before pdf_path and page range are confirmed). This gives clear sequencing and alternative selection guidance.

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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