Agent SkillsSamurAIGPT/Generative-Media-Skills › muapi-animal-video-generator

muapi-animal-video-generator

GitHub

该技能用于生成拟人化动物在现实场景中扮演人类博主的幽默短视频。通过分两阶段执行:先生成超写实动物博主图像,再基于图像结合脚本进行视频生成和口型同步,最终呈现9:16竖屏趣味内容。

library/motion/animal-video-generator/SKILL.md SamurAIGPT/Generative-Media-Skills

Trigger Scenarios

用户请求制作动物博主视频 提及 funny monkey video 或 animal vlogger 需要生成拟人化动物的创意视频

Install

npx skills add SamurAIGPT/Generative-Media-Skills --skill muapi-animal-video-generator -g -y
More Options

Non-standard path

npx skills add https://github.com/SamurAIGPT/Generative-Media-Skills/tree/main/library/motion/animal-video-generator -g -y

Use without installing

npx skills use SamurAIGPT/Generative-Media-Skills@muapi-animal-video-generator

指定 Agent (Claude Code)

npx skills add SamurAIGPT/Generative-Media-Skills --skill muapi-animal-video-generator -a claude-code -g -y

安装 repo 全部 skill

npx skills add SamurAIGPT/Generative-Media-Skills --all -g -y

预览 repo 内 skill

npx skills add SamurAIGPT/Generative-Media-Skills --list

SKILL.md

Frontmatter
{
    "name": "muapi-animal-video-generator",
    "slug": "muapi-animal-video-generator",
    "version": "1.0.0",
    "description": "Create a hilarious and ultra-realistic video of an anthropomorphic animal acting like a human vlogger in a real-world setting.",
    "acceptLicenseTerms": true
}

Animal Vlogger Video

Create a hilarious and ultra-realistic video of an anthropomorphic animal acting like a human vlogger in a real-world setting.

Inputs

Name Type Required Default Description
animal_type text no monkey The type of animal vlogging (e.g., monkey, dog, cat, bear).
location text no busy streets of Noida, India The setting for the vlog.
clothing text no a bright red t-shirt What the animal is wearing.
script text no क्या यार, कहाँ फंस गया नॉएडा में आके? इससे तो बैंगलोर ही अच्छा था. यहाँ तो बड़ी गर्मी है भाई. पसीने ही छूट गए मेरे तो. The dialogue for lip-sync.

Steps

Phase A — Generate Vlogger Image

Submit the plan with ONE step to create the base image of the animal vlogger:

  1. Image Generationmuapi image generate (model=nano-banana or nano-banana-pro):
    • Prompt: Ultra-realistic, cinematic portrait of an expressive {{animal_type}} wearing {{clothing}}, holding a selfie stick on the {{location}}. The {{animal_type}} is anthropomorphic, walking upright, and looks like a believable vlogger. Sweating slightly in the heat, highly detailed, photorealistic. Background shows a bustling street, people eating at stalls, vibrant urban details.
    • Aspect ratio: 9:16 (for vertical vlog style)

After generating the image, present it to the user.

Phase B — Video Generation

Once the image is approved, submit a second the plan with ONE step to animate it with lip-sync:

  1. Video Generationmuapi video generate or muapi video from-image (model=veo3.1-fast-image-to-video):
    • Reference Image: The generated image from Phase A.
    • Prompt: Create an ultra-realistic cinematic video featuring a lifelike {{animal_type}} vlogging with a selfie stick on the {{location}}. The film starts in selfie mode, camera slightly wide-angle. The {{animal_type}} is expressive, looks mildly disgruntled, and speaks naturally. Occasional quick zoom-in on the disappointed face. Background features busy street life, vibrant colors. Smooth gimbal-like camera motion.
    • Dialogue for Lip-Sync (if tool supports audio/lipsync): {{script}}
    • Aspect ratio: 9:16

After generation, present the final funny video.

Trigger Keywords

animal video, funny monkey video, animal vlogger, vlog video, monkey in noida


Notes for the Executing Agent

  • This recipe is LLM-orchestrated: read each phase, gather any missing inputs from the user, then call muapi CLI commands. Use muapi auth configure first if MUAPI_API_KEY is unset.
  • For model IDs without a CLI alias yet, fall back to the raw endpoint via curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}' and poll with muapi predict wait <request_id>.
  • Substitute {{input_name}} placeholders with the user's actual inputs before issuing each call.

Version History

  • d4ce293 Current 2026-07-25 11:20

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Version
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Indexed
2026-07-25 11:20

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