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muapi-one-shot-video skill

by SamurAIGPT·SamurAIGPT/Generative-Media-Skills·4.3k stars·MIT

Generate a single continuous cinematic shot video — no cuts, one seamless flowing scene with dramatic lighting and motion.

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Install the muapi-one-shot-video skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description. 

git clone --depth 1 https://github.com/SamurAIGPT/Generative-Media-Skills.git /tmp/Generative-Media-Skills
mkdir -p ~/.claude/skills
cp -r /tmp/Generative-Media-Skills/library/motion/one-shot-video ~/.claude/skills/muapi-one-shot-video
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

One-Shot Video

Generate a single continuous cinematic shot video — no cuts, one seamless flowing scene with dramatic lighting and motion.

Inputs

Steps

Phase A — Generate the One-Shot Video

Submit the plan with ONE step:

  1. One-shot video — If {{reference_image}} is provided, use muapi video generate (model=veo3.1-image-to-video); otherwise use muapi video generate (model=veo3.1-text-to-video).
  • Prompt: {{scene}}, one continuous uncut shot, no transitions, camera slowly moves through scene, {{style}}, ultra cinematic, film grain, 4K quality
  • Aspect ratio: {{aspect_ratio}}
  • Duration: {{duration}}

After generation, present the video and suggest:

  • A second angle variation
  • Adding ambient sound with mmaudio-v2-video-to-video

Notes

  • Emphasize "no cuts, no transitions" in the prompt for true one-shot feel.
  • For portrait/vertical style (9:16), add "vertical format, smartphone framing" to the prompt.
  • If the scene involves a person, suggest kling-v3.0-pro-image-to-video as an alternative for better human motion.

Trigger Keywords

one shot video, single take, continuous video, one take, cinematic shot, seamless video

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 MUAPIAPIKEY 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/ -H "x-api-key: $MUAPIAPIKEY" -H 'content-type: application/json' -d '{...}' and poll with muapi predict wait .
  • Substitute {{input_name}} placeholders with the user's actual inputs before issuing each call.

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