No red flags found in any of the 11 categories β no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by Ladbaby · Codex Skill · ★ 92
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is PyOmniTS safe to install? View the security audit →
A Researcher&Agent-Friendly Framework for Time Series Analysis. Train Any Model on Any Dataset. π Time series analysis leaderboard is now available on our π€ Hugging Face space. Discover the performance of different models! This is also the official repository for the following paper: Learning Recursive Multi-Scale Representations for Irregular Multivariate Time Series Forecasting (ICLR 2026) [[poster]](https://iclr.cc/virtual/2026/poster/10010222) [[OpenReview]](https://openreview.net/forum?id=JEIDxiTWzB) [[arXiv]](https://arxiv.org/abs/2602.21498) HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series Forecasting (ICML 2025) [[poster]](https://icml.cc/virtual/2025/poster/43741) [[OpenReview]](https://openreview.net/f
| Stars | 92 |
| Forks | 13 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 56.2728840568281/100 |
| Last Updated | 2026-08-08 |
| Created | 2025-05-20 |
| Platforms | claude-code, cli, codex, gemini, python |
| Est. Tokens | ~16k |
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PyOmniTS is π¬ A Researcher&Agent-Friendly Framework for Time Series Analysis. Train Any Model on Any Dataset!. It is categorized as a Codex Skill with 92 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 92 stars and 13 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 agent-skills, ai-skills, kindly-web-search-mcp-server. Each offers a different approach to the same problem space β compare them side-by-side by stars, quality score, and community activity.