Apply production-ready Deepgram SDK patterns for TypeScript and Python. Use when implementing Deepgram integrations, refactoring SDK usage, or establishing team coding standards for Deepgram. Trigger with phrases like "deepgram SDK patterns", "deepgram best practices", "deepgram code patterns", "idiomatic deepgram", "deepgram typescript".
This skill enables Claude to track and manage AI/ML model versions using the model-versioning-tracker plugin. It should be used when the user asks to manage model versions, track model lineage, log model performance, or implement version control for AI/ML models. Use this skill when the user mentions "track versions", "model registry", "MLflow", or requests assistance with AI/ML model deployment and management. This skill facilitates the implementation of best practices for model versioning, automation of model workflows, and performance optimization.
Feature Engineering Helper - Auto-activating skill for ML Training. Triggers on: feature engineering helper, feature engineering helper Part of the ML Training skill category.
Diagnose and fix common Deepgram errors and issues. Use when troubleshooting Deepgram API errors, debugging transcription failures, or resolving integration issues. Trigger with phrases like "deepgram error", "deepgram not working", "fix deepgram", "deepgram troubleshoot", "transcription failed".
Build LangChain chains and prompts for structured LLM workflows. Use when creating prompt templates, building LCEL chains, or implementing sequential processing pipelines. Trigger with phrases like "langchain chains", "langchain prompts", "LCEL workflow", "langchain pipeline", "prompt template".
Model Checkpoint Manager - Auto-activating skill for ML Training. Triggers on: model checkpoint manager, model checkpoint manager Part of the ML Training skill category.
PROACTIVE AUTO-LOADING: Automatically detects and loads AGENTS.md files from the current working directory when starting a session or changing directories. This skill ensures agent-specific instructions are incorporated into Claude Code's context alongside CLAUDE.md, enabling specialized agent behaviors. Triggers automatically when Claude detects it's working in a directory, when starting a new session, or when explicitly requested to "load agent context" or "check for AGENTS.md file".
Configure and select AI models in Cursor. Triggers on "cursor model", "cursor gpt", "cursor claude", "change cursor model", "cursor ai model". Use when working with cursor model selection functionality. Trigger with phrases like "cursor model selection", "cursor selection", "cursor".
Apply production-ready Fireflies.ai SDK patterns for TypeScript and Python. Use when implementing Fireflies.ai integrations, refactoring SDK usage, or establishing team coding standards for Fireflies.ai. Trigger with phrases like "fireflies SDK patterns", "fireflies best practices", "fireflies code patterns", "idiomatic fireflies".
Implement advanced model routing with A/B testing. Use when optimizing model selection or running experiments. Trigger with phrases like 'openrouter a/b test', 'model experiment', 'openrouter routing', 'model comparison'.
Build check model availability and implement fallback chains. Use when building resilient systems or handling model outages. Trigger with phrases like 'openrouter availability', 'openrouter fallback', 'openrouter model down', 'openrouter health check'.
Create a minimal working Lindy AI agent example. Use when starting a new Lindy integration, testing your setup, or learning basic Lindy API patterns. Trigger with phrases like "lindy hello world", "lindy example", "lindy quick start", "simple lindy agent".
This skill enables Claude to optimize machine learning model hyperparameters using grid search, random search, or Bayesian optimization. It is used when the user requests hyperparameter tuning, model optimization, or improvement of model performance. The skill analyzes the current context, generates code for the specified search strategy, handles data validation and errors, and provides performance metrics. Trigger terms include "tune hyperparameters," "optimize model," "grid search," "random search," and "Bayesian optimization."
This skill empowers Claude to build AutoML pipelines using the automl-pipeline-builder plugin. It is triggered when the user requests the creation of an automated machine learning pipeline, specifies the use of AutoML techniques, or asks for assistance in automating the machine learning model building process. The skill analyzes the context, generates code for the ML task, includes data validation and error handling, provides performance metrics, and saves artifacts with documentation. Use this skill when the user explicitly asks to "build automl pipeline", "create automated ml pipeline", or needs help with "automating machine learning workflows".
Pytorch Model Trainer - Auto-activating skill for ML Training. Triggers on: pytorch model trainer, pytorch model trainer Part of the ML Training skill category.
This skill enables Claude to construct and evaluate classification models using provided datasets or specifications. It leverages the classification-model-builder plugin to automate model creation, optimization, and reporting. Use this skill when the user requests to "build a classifier", "create a classification model", "train a classification model", or needs help with supervised learning tasks involving labeled data. The skill ensures best practices are followed, including data validation, error handling, and performance metric reporting.
Manage master Cursor AI chat interface for code assistance. Triggers on "cursor chat", "cursor ai chat", "ask cursor", "cursor conversation", "chat with cursor". Use when working with cursor ai chat functionality. Trigger with phrases like "cursor ai chat", "cursor chat", "cursor".
Implement Deepgram callback and webhook handling for async transcription. Use when implementing callback URLs, processing async transcription results, or handling Deepgram event notifications. Trigger with phrases like "deepgram callback", "deepgram webhook", "async transcription deepgram", "deepgram events", "deepgram notifications".
Create and manage custom prompt libraries for Cascade. Activate when users mention "custom prompts", "prompt library", "prompt templates", "cascade prompts", or "prompt management". Handles prompt library creation and organization. Use when working with windsurf custom prompts functionality. Trigger with phrases like "windsurf custom prompts", "windsurf prompts", "windsurf".
This skill trains machine learning models using automated workflows. It analyzes datasets, selects appropriate model types (classification, regression, etc.), configures training parameters, trains the model with cross-validation, generates performance metrics, and saves the trained model artifact. Use this skill when the user requests to "train" a model, needs to evaluate a dataset for machine learning purposes, or wants to optimize model performance. The skill supports common frameworks like scikit-learn.
Azure Ml Deployer - Auto-activating skill for ML Deployment. Triggers on: azure ml deployer, azure ml deployer Part of the ML Deployment skill category.
This skill automates the adaptation of pre-trained machine learning models using transfer learning techniques. It is triggered when the user requests assistance with fine-tuning a model, adapting a pre-trained model to a new dataset, or performing transfer learning. It analyzes the user's requirements, generates code for adapting the model, includes data validation and error handling, provides performance metrics, and saves artifacts with documentation. Use this skill when you need to leverage existing models for new tasks or datasets, optimizing for performance and efficiency.
This skill enables Claude to validate the ethical implications and fairness of AI/ML models and datasets. It is triggered when the user requests an ethics review, fairness assessment, or bias detection for an AI system. The skill uses the ai-ethics-validator plugin to analyze models, datasets, and code for potential biases and ethical concerns. It provides reports and recommendations for mitigating identified issues, ensuring responsible AI development and deployment. Use this skill when the user mentions "ethics validation", "fairness assessment", "bias detection", "responsible AI", or related terms in the context of AI/ML.
Model Pruning Helper - Auto-activating skill for ML Deployment. Triggers on: model pruning helper, model pruning helper Part of the ML Deployment skill category.
