Skills Plugins MCP Prompt Model 博客 我的中心

muapi-character-story-video

Create a multi-part animated story video by first establishing a consistent character and then generating sequential scenes and animating them.

DeepseekModel Curated skill Quality Excellent · 90 v1.0.0

Get

https://deepseekmodel.com/api/download.php?id=samuraigpt-generative-media-skills-library-motion-character-story-video-skill-md&format=skill
Download .skill Standard format with system_prompt and model_config, ready for any agent framework
The actual content of the system_prompt field in the .skill file.
slug muapi-character-story-video name muapi-character-story-video version 1.0.0 description Create a multi-part animated story video by first establishing a consistent character and then generating sequential scenes and animating them. acceptLicenseTerms true Character Story Video Create a multi-part animated story video by first establishing a consistent character and then generating sequential scenes and animating them. Inputs Name Type Required Default Description character_description text yes — Description of the main character (e.g. "a cute piglet wearing a leather aviator jacket and goggles"). story_premise text yes — The overall story arc (e.g. "building a jetpack and flying to space"). reference_image image_url no — Optional starting image of the character to maintain consistency. Steps This skill involves multiple phases to build a cohesive narrative. Phase A — Character Establishment If {{reference_image}} is NOT provided, submit the plan with ONE step to create the character: Character Creation — muapi image generate (model= nano-banana-pro ): Prompt: {{character_description}}, introducing the main character, cinematic lighting, highly detailed, Pixar 3D animation style. Aspect ratio: 4:5 or 1:1 If {{reference_image}} IS provided, use it as the established character and proceed to Phase B. After generation, ask the user to confirm the character design before proceeding. Phase B — Sequential Scene Generation Once the character is established, create the story beats (e.g., Scene 1, Scene 2, Scene 3). Submit the plan using muapi image edit (model= nano-banana-2-edit or flux-kontext-pro-i2i ) to maintain character consistency. Use the established character image as the reference for ALL these steps. Scene 1 (Beginning) Reference: Character Image Prompt: The character ({{character_description}}) in the first scene of the story: [Describe the beginning of {{story_premise}}]. Cinematic lighting, Pixar 3D animation style, storybook illustration. Scene 2 (Middle) Reference: Character Image Prompt: The character ({{character_description}}) in the second scene: [Describe the climax or middle action of {{story_premise}}]. Cinematic lighting, Pixar 3D animation style, storybook illustration. Scene 3 (End) Reference: Character Image Prompt: The character ({{character_description}}) in the final scene: [Describe the resolution of {{story_premise}}]. Cinematic lighting, Pixar 3D animation style, storybook illustration. Note: All scenes should be generated in parallel or sequentially depending on the story flow. After generating the scenes, present them to the user and ask if they are ready to animate the story. Phase C — Animation (Sequel Part 1, Part 2, Part 3) Submit the plan to animate the generated scenes using an image-to-video model (e.g., kling-v3.0-pro-image-to-video or veo3.1-image-to-video ). Part 1 Video Input: Scene 1 Image Prompt: Cinematic animation of the scene, character comes to life, subtle natural movements, high quality 3D animation. Part 2 Video Input: Scene 2 Image Prompt: Cinematic animation of the scene, character comes to life, dynamic action, high quality 3D animation. Part 3 Video Input: Scene 3 Image Prompt: Cinematic animation of the scene, character comes to life, triumphant resolution, high quality 3D animation. After generating the videos, present them to the user as a multi-part story sequence. You may also suggest using the muapi predict result + ffmpeg concat tool to merge them into a single movie if requested. Trigger Keywords character story , story video , animated story , sequel video , multi part video , sequential story 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.
Keywords that activate this skill. Click one to copy it.

This skill does not provide trigger words.

The downloaded .skill package contains the following fields.
Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
source_urlSource URL (this page)
exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
.skillpro Enhanced format with scripts, tools, dependencies and hooks Download
.json Plain JSON export with system_prompt and model parameters only Download
Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

每日精选 Skill 推荐,免费送到你邮箱

输入邮箱,每天接收一个精选 AI Agent 技能推荐。完全免费,持续更新。

提交后我们会发送一封确认邮件,点击邮件里的链接才会开始收信。

完全免费,取消任意时间。我们不会发送垃圾邮件。