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| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Declare the pipeline from data source to predictor as a skrub DataOps graph. | probabl-ai/ | 138 | — | ~4.1k | Automated safety check: Pass | BSD-3-Clause | yesterday |
| 2 | Guides an agent through designing an MLOps pipeline that covers data preparation, training, validation and deployment, with DAG orchestration and reference guides. | wshobson/ | 40k | 12 repos | ~1.8k | Automated safety check: Pass | MIT | 4 days ago |
| 3 | Covers logging and viewing training metrics, histograms, model graphs, embeddings and profiles with TensorBoard in PyTorch and TensorFlow projects. | Orchestra-Research/ | 13k | 3 repos | ~3.8k | Automated safety check: Pass | MIT | 3 mo ago |
| 4 | Tracks ML experiments, versions models in the MLflow registry and covers deployment and reproducibility, with autologging for common frameworks. | Orchestra-Research/ | 13k | 2 repos | ~3.9k | Automated safety check: Pass | MIT | 3 mo ago |
| 5 | 5.Edit how to use the edit command properly | omegaml/ | 107 | — | ~206 | Automated safety check: Pass | Apache-2.0 | today |
| 6 | Read-only audit of one persisted skore report: audit/NN<stem.py (jupytext percent), 1:1 with experiments/ and journal/. | probabl-ai/ | 138 | — | ~9.4k | Automated safety check: Pass | BSD-3-Clause | yesterday |
| 7 | Designs ML pipeline infrastructure: experiment tracking with MLflow or Weights & Biases, Kubeflow and Airflow orchestration, Feast feature stores and model validation gates. | Jeffallan/ | 12k | — | ~1.9k | Automated safety check: Pass | MIT | 6 days ago |
| 8 | Shows how to log ML runs, configs, metrics and media with SwanLab and view them in cloud, local or self-hosted dashboards. | Orchestra-Research/ | 13k | — | ~2.4k | Automated safety check: Pass | MIT | 3 mo ago |
| 9 | Machine learning engineer expert for PyTorch, scikit-learn, model evaluation, and MLOps | RightNow-AI/ | 18k | — | ~987 | Automated safety check: Pass | Apache-2.0 | 3 mo ago |
| 10 | Data pipelines, feature stores, and embedding generation for AI/ML systems. | ancoleman/ | 526 | — | ~3.5k | Automated safety check: Pass | MIT | 10 mo ago |
| 11 | Agent Platform Model Registry Management. An agent skill from google/skills. | google/ | 21k | — | ~2.6k | Automated safety check: Pass | Apache-2.0 | today |
| 12 | 12.Nemo Curator Curate LLM training data: dedupe, filter, PII redaction. An agent skill from Luciole-Studio/Misaka-Agent. | Luciole-Studio/ | 158 | 1 repo | ~2.6k | Automated safety check: Pass | MIT | yesterday |
| 13 | Design and implement a complete ML pipeline for: $ARGUMENTS. An agent skill from aiskillstore/marketplace. | aiskillstore/ | 430 | 7 repos | ~2.6k | Automated safety check: Pass | No licence | today |
| 14 | Train ML models on Databricks. An agent skill from databricks/databricks-agent-skills. | databricks/ | 345 | — | ~4.6k | Automated safety check: Pass | Unknown | today |
| 15 | Pick how to write a figure before custom plot code. An agent skill from probabl-ai/skills. | probabl-ai/ | 138 | — | ~785 | Automated safety check: Pass | BSD-3-Clause | yesterday |
| 16 | Literature and web research for an ML methodology concern (EDA extra measurements, leakage, transforms, feature engineering, learner family), or an EDA extra-analysis survey from JOURNAL plus… | probabl-ai/ | 138 | — | ~1.1k | Automated safety check: Pass | BSD-3-Clause | yesterday |
| 17 | A skill your agent uses when the user asks to "design an experiment", "build a predictive model", "run A/B test analysis", "perform causal inference", "engineer features", "evaluate model… | borghei/ | 886 | — | ~1.7k | Automated safety check: Pass | MIT | 2 days ago |
| 18 | Canonical backlog loop step. An agent skill from probabl-ai/skills. | probabl-ai/ | 138 | — | ~3.4k | Automated safety check: Pass | BSD-3-Clause | yesterday |
| 19 | Guide for experiment tracking tool setup (MLflow, Weights & Biases, etc.), reproducibility assurance, model registry, and experiment comparison methodology. | revfactory/ | 1.3k | — | ~1.4k | Automated safety check: Pass | Apache-2.0 | 6 mo ago |
| 20 | 20.Cortex Model Build an ML pipeline — from data to trained model to serving endpoint. | jeremylongshore/ | 2.8k | — | ~1.2k | Automated safety check: Notes | MIT | today |
| 21 | Automate ML workflows with Airflow, Kubeflow, MLflow. An agent skill from secondsky/claude-skills. | secondsky/ | 227 | — | ~3.2k | Automated safety check: Pass | MIT | 11 days ago |
| 22 | 22.ML Pipeline MANDATORY whenever a task involves training, fine-tuning, tuning, or evaluating a machine-learning model on data (tabular, time series, text, images — any modality). | hashgraph-online/ | 1.3k | — | ~3.2k | Automated safety check: Pass | Apache-2.0 | today |
| 23 | A full ML pipeline where an agent team collaborates to perform data preparation, model design, training, evaluation, and deployment readiness. | revfactory/ | 1.3k | — | ~1.9k | Automated safety check: Pass | Apache-2.0 | 6 mo ago |