by Ladbaby · Codex Skill · ★ 67
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔬 A Researcher&Agent-Friendly Framework for Time Series Analysis. Train Any Model on Any Dataset!
| Stars | 67 |
| Forks | 10 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 34.25/100 |
| Open Issues | 3 |
| Last Updated | 2026-05-01 |
| Created | 2025-05-20 |
| Platforms | claude-code, cli, codex, gemini, python |
| Est. Tokens | ~549k |
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PyOmniTS is 🔬 A Researcher&Agent-Friendly Framework for Time Series Analysis. Train Any Model on Any Dataset!. It is categorized as a Codex Skill with 67 GitHub stars.
PyOmniTS is primarily written in Python. It covers topics such as benchmarking, claude-code, codex.
You can find installation instructions and usage details in the PyOmniTS GitHub repository at github.com/Ladbaby/PyOmniTS. The project has 67 stars and 10 forks, indicating an active community.
PyOmniTS is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to PyOmniTS on Agent Skills Hub include create-llm, moonshot, bocoel. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.