Muapi Action Figure Generator Agent Skill
Convert a photo of a person into a custom 3D action figure, complete with collectible toy packaging.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/SamurAIGPT/Generative-Media-Skills --skill muapi-action-figure-generatorThe instruction itself
6 sections, as written by the authorAction Figure Generator
Convert a photo of a person into a custom 3D action figure, complete with collectible toy packaging.
Inputs
| Name | Type | Required | Default | Description |
|:---|:---|:---|:---|:---|
| user_image | image_url | yes | — | A clear photo of the person to be turned into an action figure. |
| toy_theme | text | no | superhero | The theme of the action figure (e.g. superhero, doctor, explorer, sci-fi). |
Steps
Phase A — Action Figure Creation
If {{user_image}} is not provided, ask the user to upload their photo.
Once the photo is available, submit the plan with ONE step to generate the action figure:
- Action Figure Generation —
muapi image edit(model=nano-banana-2-edit): - Reference Image:
{{user_image}} - Prompt:
A high-quality 3D stylized action figure based on the person in the input image. The action figure should maintain the person's likeness (face, hairstyle, skin tone) but be rendered as a plastic toy with visible joints and a semi-glossy finish. The character is dressed in a {{toy_theme}} outfit. The figure is displayed inside its original collectible cardboard and plastic blister packaging. The packaging has the person's name printed on it and features clean, modern graphic design. Soft studio lighting, realistic plastic textures, 8k resolution, cinematic look. - Aspect ratio: 1:1 or 4:5
Present the generated action figure to the user. You can also suggest creating different themes (e.g., changing the character from a doctor to a space explorer).
Trigger Keywords
action figure, custom toy, toy packaging, character toy, collectible figure
Notes for the Executing Agent
- This recipe is LLM-orchestrated: read each phase, gather any missing inputs from the user, then call
muapiCLI commands. Usemuapi auth configurefirst ifMUAPI_API_KEYis 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 withmuapi predict wait <request_id>. - Substitute
{{input_name}}placeholders with the user's actual inputs before issuing each call.
Other skills for the same job
different authors, same section of the catalogue
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.
Downloads videos from YouTube and other platforms for offline viewing, editing, or archival. Handles various formats and quality options.
Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.
Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
How to use it
Take samuraigpt/muapi-action-figure-generator from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.