Skill UI

This guide details the process of deploying production-grade inference services on CoreWeave using KServe. It covers setting up autoscaling, GPU scheduling, and implementing scale-to-zero functionality for efficient ML model serving endpoints. Ideal for MLOps engineers deploying large language models (LLMs) or other complex AI models in a production environment.

A comprehensive guide for authors targeting top-tier conferences like ICAPS. It assists in re-framing automated planning and scheduling manuscripts, providing detailed advice on structuring the contribution, identifying necessary empirical/theoretical evidence, optimizing scope vocabulary, and strategically positioning the work against related venue submissions. Use this tool for venue selection, manuscript calibration, and strengthening the submission narrative.

Reads a session goal, routes it to the right phase, and compiles Claude Managed Agent loops or workflows. Supports goal tracking, bounded iteration, cron scheduling, and BYOK hand-off.

Schedule AI agent runs safely with cron, systemd timers, external clocks, or built-in schedulers such as Hermes, covering heartbeat patterns, permissions, overlap locks, stop conditions and verification to avoid unsafe tight autonomous timers.

Learn to orchestrate AI/ML pipelines for data ingestion, model training, batch inference, and RAG indexing using tools like Prefect, Airflow, or Dagster. This skill covers scheduling recurring tasks, managing dependencies between data preparation and model serving, and building reliable, observable workflows for production AI systems.