{"name":"sprite-gen: Generate Game Sprites and Animation Atlases","description":"sprite-gen is a Python CLI and Codex/Claude skill that turns a still image into transparent game sprites, runtime atlases, or motion loops. Its video pipeline uses Grok Imagine to animate stills, then extracts and prepares frames for game use.","github":"https://github.com/aldegad/sprite-gen","url":"https://osrepos.com/repo/aldegad-sprite-gen","source":"osrepos.com","sourceDescription":"This repository profile is provided by osrepos.com, an open source repository discovery platform.","repositoryProfile":"https://osrepos.com/repo/aldegad-sprite-gen","generatedFor":"open source discovery and AI-assisted research","markdown":"https://osrepos.com/repo/aldegad-sprite-gen.md","json":"https://osrepos.com/repo/aldegad-sprite-gen.json","topics":["python","cli","ai-agents","game-development","sprite-generation","sprite-atlas","2d-animation"],"keywords":["python","cli","ai-agents","game-development","sprite-generation","sprite-atlas","2d-animation"],"stars":null,"summary":"sprite-gen is a Python CLI and Codex/Claude skill that turns a still image into transparent game sprites, runtime atlases, or motion loops. Its video pipeline uses Grok Imagine to animate stills, then extracts and prepares frames for game use.","content":"## Overview\n\nsprite-gen is a Python CLI and Codex/Claude skill for turning one character image into game-ready sprite assets. Its atlas pipeline generates state rows, cleans up transparency, extracts frames, and builds an atlas with a machine-readable layout manifest. For animated loops, it uses Grok Imagine to create video clips and then cuts them into transparent animations.\n\nThe tool targets game developers and coding-agent users who need more than a generated sprite sheet: it includes frame extraction, optional visual curation, runtime-oriented exports, and tools for processing existing assets. Generation uses provider credentials supplied by the user, while some workflows also rely on external command-line tools.\n\n## Key Features\n\n- Generate sprite states from a base image, then extract transparent frames and compose a runtime atlas with frame-layout metadata.\n- Create per-state motion loops from still images using Grok Imagine video generation and frame-processing commands.\n- Review, reject, or adjust generated frames in an optional curation webview before composing an atlas.\n- Apply deterministic palette-based recoloring and export atlases for formats including Aseprite, Phaser, and Flame.\n- Process existing art with utilities for cutouts, sheet slicing, atlas unpacking, repeating backgrounds, and projected shadows.\n- Inspect animation timing and contact evidence, and optionally compose existing assets into rendered scenes.\n\n## Use Cases\n\n- A solo game developer wants to turn one character illustration into an atlas with explicit frame rectangles for a game engine.\n- A developer using Codex or Claude wants an agent-accessible workflow to generate, inspect, and prepare sprite assets.\n- An artist needs transparent idle, attack, or other motion loops from a still image and is prepared to use the video pipeline.\n- A team with existing sprite sheets wants to slice, recolor, export, or inspect assets without regenerating them.\n\n## Our Take\n\nsprite-gen is a broad, actively changing asset pipeline that offers useful game-specific processing, but its recent pace and highly concentrated contributions call for review before a team depends on it.\n\n**Good fit if:**\n- You need a Python-based workflow for turning still images into transparent sprites, atlases, or loops.\n- Your workflow can use the required provider credentials and, for video processing, the documented external tools.\n- You value frequent releases and can keep up with a young project that is changing quickly.\n\n**Look elsewhere if:**\n- You need a mature project with contributions spread across multiple maintainers; most development comes from one contributor.\n- Your environment cannot run Python 3.11 or newer.\n- You need a sprite workflow that does not depend on external image or video generation providers for generated assets.\n\n## Project Health\n\n| Signal | Value |\n|---|---|\n| Status | **New**: less than six months old and changing fast |\n| Last commit | 2026-10-21 (2 days ago) |\n| Commits, last 90 days | 100+ |\n| Releases, last 12 months | 69 (latest v2.45.3, 2026-10-21) |\n| Contributors | 5 (top contributor: 100% of commits) |\n| Issues closed, last 90 days | 0+ |\n| Pull requests merged, last 90 days | 97 (typically merged in 0 days) |\n| Project age | 5 months |\n\nChecked on 2026-10-23 with the GitHub API.\n\n## Project Facts\n\n- Language: Python\n- License: Apache-2.0\n- Stars: 3k\n- Forks: 325\n- Topics: 2d-game, ai-tools, claude-code, codex, game-dev, gamedev, pixel-art, sprite-generation\n- Archived: no\n\n## What You Need\n\nDetected in the repository:\n\n- Python >=3.11 (from pyproject.toml)\n- A test suite\n\n## Getting Started\n\n```bash\npython3 -m venv .venv && source .venv/bin/activate\npip install -e .\nsprite-gen --help\n```\n\nSee the [README](https://github.com/aldegad/sprite-gen) for pipeline commands, provider setup, and workflow documentation.\n\n## License in Plain Words\n\n**Apache-2.0** (permissive).\n\n- Commercial use: yes\n- Modify and redistribute: yes\n- You must keep: the license, the NOTICE file and a note of your changes\n- Share your changes: no\n- Includes an explicit patent grant from the contributors\n\nA summary, not legal advice: the LICENSE file is what applies.\n\n## Considerations\n\nThe project is less than six months old and is changing quickly, with recent commits and frequent releases. Although it has several contributors, nearly all measured contributions come from one person, so maintenance continuity is a consideration. The measured health data reports tests but no CI. The atlas workflow needs Python 3.11 or newer; video workflows additionally document requirements such as `ffmpeg`, `img2webp`, and a Grok login or API key. Generated assets rely on user-provided credentials, and API-key calls may incur per-call costs. The README also cautions that facing detection can be wrong and that cyclic locomotion remains experimental unless motion QA passes.","metrics":{"detailViews":3,"githubClicks":2},"dates":{"published":null,"modified":"2026-10-23T14:51:31.000Z"}}