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Use PROACTIVELY when creating research reports, experiment writeups, technical whitepapers, or empirical study documentation. Orchestrates the complete benchmark report pipeline with structure, diagrams, hi-res...
RAN performance analysis with bottleneck detection, cognitive consciousness, and temporal reasoning for deep performance insights. Use when analyzing RAN performance, detecting bottlenecks, optimizing network e...
Causal inference and discovery for RAN optimization with Graphical Posterior Causal Models (GPCM), intervention effect prediction, and causal relationship learning. Discovers causal patterns in RAN data and ena...
Reinforcement learning engineering for RAN systems with policy gradients, experience replay, and AgentDB integration. Implements hybrid RL with multi-objective optimization for energy, mobility, coverage, and c...
AgentDB integration specialist for RAN ML systems with vector storage, pattern recognition, and distributed training coordination. Achieves 150x faster search,
ML research for RAN with reinforcement learning, causal inference, and cognitive consciousness integration. Use when researching ML algorithms for RAN optimization, implementing reinforcement learning agents, d...
Structured multi-step reasoning for complex problems using MCP. Use this skill when facing architectural decisions, performance bottlenecks, complex debugging, system design challenges, or any problem requiring...
Design AI agents with recommended patterns and architectures
Analyze and improve existing prompts for better performance
Cloud Run AI Engine deployment workflow with free tier optimization. Triggers when user requests Cloud Run deployment, AI engine deploy, or production release. Use for deploying AI Engine to Google Cloud Run.
Automated 2-AI verification result documentation and export workflow. Triggers when user requests AI verification report export, documentation of findings, or saving cross-validation results. Use after completi...
KubeAI, GPU operators, and model serving patterns for AI/ML infrastructure on Kubernetes.
Assess and report on AI tool subscriptions, usage patterns, and cost-effectiveness. Use for reviewing AI subscriptions, analyzing tool usage, optimizing AI spend.
Neural network training and deployment in Flow Nexus cloud. Use for distributed ML training, model inference, and neural network lifecycle management.
YAML for configuration-driven engineering workflows, model setup, and analysis parameters
Build AI agents with Google ADK Python (Agent Development Kit). Use for multi-agent systems, workflow agents (sequential/parallel/loop), Vertex AI deployment, tool integration, human-in-the-loop.
Data engineering agent for ETL pipelines, data warehousing, and analytics
Expert data science guidance for analytics, data processing, visualization, statistical analysis, machine learning, and AI integration. Use when analyzing data, building ML models, creating visualizations, proc...
Evaluate agent and LLM outputs. Use when asked to evaluate agent performance, build evaluation frameworks, implement LLM-as-judge, compare model outputs, create rubrics, mitigate evaluation bias, or design eval...
Elite context engineering specialist for AI agents - token optimization, degradation patterns, compression, memory systems, multi-agent coordination, vector databases, knowledge graphs, RAG systems, and enterpr...
Perform comprehensive data analysis, statistical modeling, and data visualization by writing and executing self-contained Python scripts. Use when you need to analyze datasets, perform statistical tests, create...
Track ML experiments with proper logging and reproducibility. Use when training models or running experiments.
Use when building AI agents with Google's Agent Development Kit (ADK) Python - multi-agent systems, workflow agents, tool integration, Vertex AI deployment, or agent evaluation.
Guide for evaluating models using scenarios specified by the user. This skill should be used when users ask Claude to evaluate a model using a specific scenario.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.