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Headdao
by Headdao

topic_to_video

Generate a presentation from a topic. Enable include_scripts for narration or include_video for an MP4 video, then poll check_status for the result.

Instructions

One-click pipeline: create a presentation from a topic. Default produces slides only. Set include_scripts=true for narration scripts, include_video=true for full MP4 video. Poll check_status afterward.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
styleNoVisual style: 'professional', 'playful', 'minimalist'
topicYesThe topic or prompt for the presentation
languageNoLanguage code: 'zh-TW', 'zh-CN', 'en', 'ja' (default: 'zh-TW')
tts_voiceNoTTS voice name/ID from the chosen provider
image_sizeNoImage resolution: '1K', '2K', or '4K' (default: '2K')
slides_countNoNumber of slides to generate (default: 8)
tts_providerNoTTS provider: 'gemini', 'cosyvoice', 'azure'
include_videoNoGenerate TTS audio and compile MP4 video, implies include_scripts (default: false)
include_scriptsNoGenerate narration scripts for each slide (default: false)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.2

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden. It discloses that the tool is asynchronous ('Poll check_status afterward'), that it produces slides by default, and that scripts and video are opt-in via flags. It does not detail side effects or errors, but covers the key behavioral traits needed to invoke and manage the operation.

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?

Three sentences with no filler. It front-loads the core purpose, then the default behavior, then the two key flags, and finally the required follow-up. Every sentence contributes actionable information.

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?

The description is adequate for a 9-parameter tool with no output schema and no annotations. It explains the pipeline behavior, conditional outputs, and post-call polling. Minor gaps remain around result retrieval and relationship to step-level siblings, but the schema carries the parameter detail and the description provides enough operational context.

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 the baseline is 3. The description adds a useful high-level summary of the include_scripts and include_video flags, but it does not provide meaning beyond the schema's parameter descriptions. No parameter documentation gap exists, so no higher score is warranted.

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 clearly states a specific action and resource: 'create a presentation from a topic' via a 'one-click pipeline'. It also clarifies the default output (slides only) and optional outputs (scripts, MP4 video), which distinguishes it from granular sibling tools like render_slides and generate_video.

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

Usage Guidelines4/5

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

The description gives clear usage context: use this for an end-to-end topic-to-presentation pipeline, set include_scripts for narration scripts, set include_video for video, and poll check_status afterward. It does not explicitly mention when not to use it or name alternative step tools, but the pipeline framing and follow-up guidance are sufficient.

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