io.github.Headdao/slidemaster-mcp

generate_outline

Generate a structured presentation outline from any topic, providing slide titles and descriptions to guide slide creation.

Instructions

Generate a presentation outline from a topic. Returns a list of slide titles and descriptions that can be used to create slides.

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": {
      "topic": "<topic>"
    },
    "name": "generate_outline"
  }
}

Input Schema

Name	Required	Description
`style`	No	Visual style hint, e.g. 'professional', 'playful', 'minimalist'
`topic`	Yes	The topic or prompt to generate an outline for
`language`	No	Language code: 'zh-TW', 'zh-CN', 'en', 'ja' (default: 'zh-TW')
`slides_count`	No	Number of slides to generate (default: 8)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.1.2Sep 6, 2026

TDQS

A3.8/5.0

Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It does explain the core behavior: it returns slide titles and descriptions, and the phrase 'can be used to create slides' suggests the outline is not itself a finished slide deck. However, it omits any mention of side effects, persistence, or whether the outline is tied to an existing project.

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 two sentences with no filler. The core action is front-loaded, and the output expectation is stated immediately. Every sentence earns its place without repeating schema details.

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

Completeness4/5

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

For a straightforward content-generation tool with fully documented parameters and no output schema, the description adequately captures both input and return value. It could be more complete by explaining how the returned outline is intended to be used downstream, but the essential information for calling the tool correctly is present.

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 description coverage is 100%, so all four parameters are already documented in the schema. The description adds little beyond reinforcing that the outline is generated 'from a topic,' so it stays at the baseline for parameter semantics.

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 opens with a specific verb and resource: 'Generate a presentation outline from a topic.' It then clarifies the return value as a list of slide titles and descriptions, which distinguishes it clearly from sibling tools like generate_script or generate_video that produce different artifacts.

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

Usage Guidelines3/5

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

The description implies the tool is meant for producing an outline before slide creation, but it never explicitly states when to prefer this tool over generate_script, topic_to_video, or other siblings. No when-to-use or when-not-to-use guidance is provided, so usage context is only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.