Analytics & Monitoring Agent Skills for ChatGPT

A/B test design — produce an experiment spec with hypothesis, primary metric, MDE, sample size, run time, and decision rule.

Battle-tested PyTorch training recipes for all domains — LLMs, vision, diffusion, medical imaging, protein/drug discovery, spatial omics…

Provides guidance for interpreting and manipulating neural network internals using nnsight with optional NDIF remote execution.

Fine-tune and serve Physical Intelligence OpenPI models (pi0, pi0-fast, pi0.5) using JAX or PyTorch backends for robot policy inference…

Check session status and measure goal drift

PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model…

Analyze Rails code for performance issues, optimize queries, identify bottlenecks, and ensure scalability.

Scalable data processing for ML workloads.

Guides researchers through structured ideation frameworks to discover high-impact research directions.

Identify anomalous sessions using Agent Monitor data — cost outliers from the pricing engine, token anomalies (cache miss spikes…

Analyzes pipeline coverage, tracks forecast accuracy with MAPE, and calculates GTM efficiency metrics for SaaS revenue optimization

Brand monitoring tool for tracking mentions across social media platforms.

Generates Correlation ID propagation components for PHP 8.4.

Weekly engineering retrospective with persistent metrics — commit patterns, work sessions, code-quality trends.

Build monitoring dashboards that answer real operator questions for Grafana, SigNoz, and similar platforms.

Create a refreshable live operations artifact for customer success, support, or launch review workflows.

Analyze and engineer protein glycosylation.

Use when asked to analyze a funnel, find where users drop off, diagnose low conversion or activation rates, design a metrics framework…

Metrics architecture — produce a complete metrics plan given a product description.

Product analyst — metrics architecture, funnel analysis, A/B test design, retention, and growth measurement.

OKR trees, KPI dashboards, North Star Metric, leading/lagging indicators, and experiment design.