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Explaining Machine Learning Models

explaining-machine-learning-models

jeremylongshore/claude-code-plugins-plus-skills

Provides interpretable explanations for ML predictions using SHAP, LIME, and other techniques, helping debug model behavior, highlight feature importance, and communicate fairness insights to stakeholders.

Culture Index Interpreter

interpreting-culture-index

trailofbits/skills

Interprets Culture Index survey and profile data to explain behavioral traits, team gas/brake/glue dynamics, burnout risk, hiring profiles, coaching cues, interview trait prediction, and conflict mediation, accepting extracted JSON or verified PDF input.

Deliberate Learning Exercises

learning-opportunities

tech-leads-club/agent-skills

Offers short interactive exercises after architectural or unfamiliar work in AI-assisted coding, prompting learners with prediction, explanation, or comparison questions before revealing answers.

Prediction Monitor Assistant

prediction-monitor

jeremylongshore/claude-code-plugins-plus-skills

Prediction Monitor Assistant automates machine learning deployment monitoring tasks, offering step-by-step guidance, best-practice patterns, production-ready code and configuration generation, and validation to keep serving and inference workflows reliable.

Replicate Model Automation

replicate-automation

ComposioHQ/awesome-claude-skills

Automate Replicate AI workflows via the Composio MCP integration to inspect model schemas, run predictions (sync or async), upload input files, list versions, and manage prediction history and related assets.

Protein Language Modeling Suite

K-Dense-AI/claude-scientific-skills

Toolkit for ESM protein language models providing generative design, structure prediction, embeddings, function conditioning, and Forge-powered batch inference for protein engineering and representation tasks.

PyHealth Clinical AI Toolkit

K-Dense-AI/claude-scientific-skills

PyHealth is a Python healthcare AI toolkit for building, training, evaluating, and deploying clinical prediction models using EHR, signal, imaging, and coding data while optimizing pipelines, calibration, and interpretability.

Therapeutics Data Commons

K-Dense-AI/claude-scientific-skills

PyTDC offers curated AI-ready datasets, standardized benchmarks, and scaffold-aware splits across ADME, toxicity, interaction, and generation tasks to support therapeutic ML and pharmacological prediction workflows.

Survival Analysis Toolkit

scikit-survival

K-Dense-AI/claude-scientific-skills

Comprehensive scikit-survival guidance for handling censored data, building Cox, ensemble, and SVM survival models, and evaluating time-to-event predictions with concordance, AUC, and Brier scores, making it ideal for clinical or reliability studies in Python.

Shap Model Interpretation

K-Dense-AI/claude-scientific-skills

Explain machine learning predictions with SHAP values, generate global and local plots (beeswarm, waterfall, force), compare models, debug bias, and ship explainable AI in production.

TorchDrug Molecular GNNs

K-Dense-AI/claude-scientific-skills

TorchDrug offers PyTorch-native graph neural networks, datasets, and tasks tailored to drug discovery, protein modeling, knowledge graphs, molecular generation, and retrosynthesis, letting researchers define custom GNN architectures for property prediction and synthesis planning.

InterPro Protein Annotation

interpro-database

K-Dense-AI/claude-scientific-skills

Query InterPro for protein family, domain, and GO annotations via a REST API with Python helpers, enabling function prediction, domain architecture mapping, and evolutionary classification insights for proteomic workflows.

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