flask-ml-api-creator
Flask Ml Api Creator - Auto-activating skill for ML Deployment. Triggers on: flask ml api creator, flask ml api creator Part of the ML Deployment skill category.
Flask Ml Api Creator - Auto-activating skill for ML Deployment. Triggers on: flask ml api creator, flask ml api creator Part of the ML Deployment skill category.
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."
Optimize Vast.ai API performance with caching, batching, and connection pooling. Use when experiencing slow API responses, implementing caching strategies, or optimizing request throughput for Vast.ai integrations. Trigger with phrases like "vastai performance", "optimize vastai", "vastai latency", "vastai caching", "vastai slow", "vastai batch".
This skill enables Claude to deploy machine learning models to production environments. It automates the deployment workflow, implements best practices for serving models, optimizes performance, and handles potential errors. Use this skill when the user requests to deploy a model, serve a model via an API, or put a trained model into a production environment. The skill is triggered by requests containing terms like "deploy model," "productionize model," "serve model," or "model deployment."
Plan and execute LangChain SDK upgrades and migrations. Use when upgrading LangChain versions, migrating from legacy patterns, or updating to new APIs after breaking changes. Trigger with phrases like "upgrade langchain", "langchain migration", "langchain breaking changes", "update langchain version", "langchain 0.3".
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".
Execute batch inference pipeline operations. Auto-activating skill for ML Deployment. Triggers on: batch inference pipeline, batch inference pipeline Part of the ML Deployment skill category. Use when working with batch inference pipeline functionality. Trigger with phrases like "batch inference pipeline", "batch pipeline", "batch".
Execute self-learning system that captures corrections during sessions and syncs them to CLAUDE.md. Use when discussing learnings, corrections, or when the user mentions remembering something. Trigger with phrases like "remember this", "don't forget", "use X not Y", or "actually...".
Create flask ml api creator operations. Auto-activating skill for ML Deployment. Triggers on: flask ml api creator, flask ml api creator Part of the ML Deployment skill category. Use when working with APIs or building integrations. Trigger with phrases like "flask ml api creator", "flask creator", "flask".
Implement LangChain data privacy and handling best practices. Use when handling sensitive data, implementing PII protection, or ensuring data compliance in LLM applications. Trigger with phrases like "langchain data privacy", "langchain PII", "langchain GDPR", "langchain data handling", "langchain compliance".
This skill empowers Claude to construct recommendation systems using collaborative filtering, content-based filtering, or hybrid approaches. It analyzes user preferences, item features, and interaction data to generate personalized recommendations. Use this skill when the user requests to build a recommendation engine, needs help with collaborative filtering, wants to implement content-based filtering, or seeks to rank items based on relevance for a specific user or group of users. It is triggered by requests involving "recommendations", "collaborative filtering", "content-based filtering", "ranking items", or "building a recommender".
Implement Retell AI rate limiting, backoff, and idempotency patterns. Use when handling rate limit errors, implementing retry logic, or optimizing API request throughput for Retell AI. Trigger with phrases like "retellai rate limit", "retellai throttling", "retellai 429", "retellai retry", "retellai backoff".
This skill enables Claude to provide interpretability and explainability for machine learning models. It is triggered when the user requests explanations for model predictions, insights into feature importance, or help understanding model behavior. The skill leverages techniques like SHAP and LIME to generate explanations. It is useful when debugging model performance, ensuring fairness, or communicating model insights to stakeholders. Use this skill when the user mentions "explain model", "interpret model", "feature importance", "SHAP values", or "LIME explanations".
Comprehensive debugging toolkit for Lindy AI agents. Use when investigating complex issues, collecting diagnostics, or preparing support tickets. Trigger with phrases like "lindy debug", "lindy diagnostics", "lindy support bundle", "investigate lindy issue".
Configure with conditional request helper operations. Auto-activating skill for API Development. Triggers on: conditional request helper, conditional request helper Part of the API Development skill category. Use when working with conditional request helper functionality. Trigger with phrases like "conditional request helper", "conditional helper", "conditional".
Build LangChain agents with tools for autonomous task execution. Use when creating AI agents, implementing tool calling, or building autonomous workflows with decision-making. Trigger with phrases like "langchain agents", "langchain tools", "tool calling", "langchain autonomous", "create agent", "function calling".
Create a minimal working Fireflies.ai example. Use when starting a new Fireflies.ai integration, testing your setup, or learning basic Fireflies.ai API patterns. Trigger with phrases like "fireflies hello world", "fireflies example", "fireflies quick start", "simple fireflies code".
Tensorflow Serving Setup - Auto-activating skill for ML Deployment. Triggers on: tensorflow serving setup, tensorflow serving setup Part of the ML Deployment skill category.
Apply LangChain security best practices for production. Use when securing API keys, preventing prompt injection, or implementing safe LLM interactions. Trigger with phrases like "langchain security", "langchain API key safety", "prompt injection", "langchain secrets", "secure langchain".
Diagnose and fix Perplexity common errors and exceptions. Use when encountering Perplexity errors, debugging failed requests, or troubleshooting integration issues. Trigger with phrases like "perplexity error", "fix perplexity", "perplexity not working", "debug perplexity".
This skill empowers Claude to construct recommendation systems using collaborative filtering, content-based filtering, or hybrid approaches. It analyzes user preferences, item features, and interaction data to generate personalized recommendations. Use this skill when the user requests to build a recommendation engine, needs help with collaborative filtering, wants to implement content-based filtering, or seeks to rank items based on relevance for a specific user or group of users. It is triggered by requests involving "recommendations", "collaborative filtering", "content-based filtering", "ranking items", or "building a recommender".
Optimize LangChain API costs and token usage. Use when reducing LLM API expenses, implementing cost controls, or optimizing token consumption in production. Trigger with phrases like "langchain cost", "langchain tokens", "reduce langchain cost", "langchain billing", "langchain budget".
Incident response procedures for LangChain production issues. Use when responding to production incidents, diagnosing outages, or implementing emergency procedures for LLM applications. Trigger with phrases like "langchain incident", "langchain outage", "langchain production issue", "langchain emergency", "langchain down".
Diagnose and fix common LangChain errors and exceptions. Use when encountering LangChain errors, debugging failures, or troubleshooting integration issues. Trigger with phrases like "langchain error", "langchain exception", "debug langchain", "langchain not working", "langchain troubleshoot".