Analytics & Monitoring Agent Skills

Use when looking for top-solution tricks on a Kaggle competition, when needing CV-LB gap discussions, when validating a strategy against…

Standard Operating Procedure for ANY Kaggle experiment or competition entry.

Systematically replicate and learn from top Kaggle performers.

Analytics and attribution setup — tracking plan, UTM conventions, dashboard design, and attribution model selection.

Instrument an AI application with DeepEval's native tracing so its behavior is visible in Confident AI.

Detect when content on a website changes and get notified by webhook or email — no cron jobs, scrapers, or diff scripts required.

Build agentic applications with GitHub Copilot SDK.

Execute Hugging Face Hub operations using the `hf` CLI.

Fetches and references LangGraph Python documentation to build stateful agents, create multi-agent workflows, and implement…

lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.).

MemPalace — Local AI memory with 96.6% recall.

Browse and run any of the ~350 models served by the local cli-proxy-api (all OpenRouter models plus Codex).

Distributed training orchestration across clusters.

Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement.

Score any AI model on the DeepSWE coding-agent benchmark via the OpenRouter API.

Temporal graph operations on Semantica — scoped queries at a point in time, graph snapshots, node change timelines, temporal causal…

High-throughput LLM inference on NVIDIA GPUs.

Pretrain LLMs at scale with PyTorch 4D parallelism.

Track and visualize ML training experiments with Trackio.

This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging…

Deep agentic-flow@alpha integration implementing ADR-001.