Total 30,915 skills, AI & Machine Learning has 4990 skills
Showing 12 of 4990 skills
This skill should be used when the user asks to "create a replit prompt", "write a prompt for replit", "optimize for replit agent", "prepare instructions for replit", or mentions building something with Replit Agent. Transforms user requirements into optimized, structured prompts that Replit Agent understands and executes accurately with minimal iterations.
Deploy and serve TensorFlow models
Add a new tool to an existing FastMCP server with guided configuration
MCP architecture patterns, security, and memory management. Auto-loads when building MCP servers, implementing tools/resources, discussing MCP security, or working with FastMCP.
Expert in Machine Learning Operations bridging data science and DevOps. Use when building ML pipelines, model versioning, feature stores, or production ML serving. Triggers include "MLOps", "ML pipeline", "model deployment", "feature store", "model versioning", "ML monitoring", "Kubeflow", "MLflow".
Structured clarification before decisions. Use when user is in PLANNING mode, explicitly asks to plan or discuss, or when agent faces choices requiring user input. Ensures agent asks questions instead of making autonomous decisions when multiple valid approaches exist or context is missing.
Writes agent outputs to numbered thread stage files. Called by agents after domain work completes. Maps agent type to stages, updates frontmatter status, and records completion metadata. Stage 1 (1-input.md) is never written by this skill.
Reasons through problems using six cognitive modes. Applies causal (execute goals), abductive (explain observations), inductive (find patterns), analogical (transfer from similar), dialectical (resolve tensions), and counterfactual (evaluate alternatives) thinking. Use when planning, diagnosing, finding patterns, evaluating trade-offs, or exploring what-ifs. Triggers on "why did", "what if", "how should", "analyze this", "figure out".
Install and configure LSP (Language Server Protocol) for Claude Code to enable go-to-definition, find-references, and real-time diagnostics
Expert in load balancing and dynamic task allocation for multi-agent systems. Specializes in optimal routing based on agent capability, availability, and cost (Token Economics).
Expert in making multi-agent systems resilient. Specializes in detecting loops, hallucinations, and failures, and implementing self-healing workflows. Use when designing error handling for agent systems, implementing retry strategies, or building resilient AI workflows.
Expert in observing, benchmarking, and optimizing AI agents. Specializes in token usage tracking, latency analysis, and quality evaluation metrics. Use when optimizing agent costs, measuring performance, or implementing evals. Triggers include "agent performance", "token usage", "latency optimization", "eval", "agent metrics", "cost optimization", "agent benchmarking".