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Agent.ai MCP Server

by OnStartups

heygen_avatar_generate_video

Generate a talking-photo avatar video by scraping a blog URL or providing a topic or script. Returns a video ID for status polling.

Instructions

Generates a talking-photo avatar video via HeyGen. Scrapes a blog URL or uses a topic/script to create a voiceover, then submits to HeyGen V2 API. Returns a video_id for status polling.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
source_typeYesHow to generate the video script.blog_url
blog_urlNoURL of blog post to scrape (required when source_type is blog_url).
topicNoTopic idea or full script text (required when source_type is topic_or_script).
content_typeNoVideo style when using blog URL source.blog_summary
aspect_ratioYeslandscape
avatar_nameYessawyer
expressionNodefault
circle_styleNoApply circle mask to avatar.
background_colorNoHex color for video background (e.g. #FFFFFF).#FFFFFF
output_variable_nameYesVariable name for result. Access fields with {{heygen_result.video_id}}, {{heygen_result.title}}, {{heygen_result.script}}.heygen_result
Behavior3/5

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

Without annotations, the description carries full burden. It mentions scraping, voiceover creation, API submission, and returning a video_id for polling. However, it omits authentication needs, rate limits, potential costs, and error scenarios.

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, no redundancy, front-loads purpose. Every sentence adds value and fits within a concise structure.

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?

Covers key functionality and output, but lacks details on error handling, prerequisites, and full output structure. Given the complexity (10 params, no output schema, no annotations), it is adequate but not fully complete.

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 70% with good descriptions. The tool description adds little beyond restating the two source_type modes and the output video_id. Baseline 3 applies as the schema does most of the work.

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?

Clearly states it generates a talking-photo avatar video via HeyGen, with two sourcing methods (blog URL or topic/script). Distinguishes from siblings like heygen_photo_avatar_create_avatar_action which creates avatars rather than videos.

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?

Implies usage for generating avatar videos but does not explicitly compare with sibling tools like heygen_avatar_get_video_status (for polling) or other HeyGen tools. No when-not-to-use guidance provided.

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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