Analytics & Monitoring Agent Skills for Claude Code

Guides empirical heterogeneity analysis for World Economy manuscripts using open-economy and international trade theory margins.

Constructs rigorous, testable cross-border transmission mechanism analyses aligned with the publication standards of The Journal of World…

Primary Python toolkit for molecular biology.

Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files.

Run Python code in the cloud with serverless containers, GPUs, and autoscaling.

Interactive scientific and statistical data visualization library for Python.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for…

Comprehensive quantum computing toolkit for building, optimizing, and executing quantum circuits.

Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigorous statistical…

Optimal blending strategy for Kaggle competitions: 80/20 rule (re-ranking vs raw).

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

Downloads, exports, and inspects existing Arize traces and spans to understand what an LLM app is doing or debug runtime issues.

AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.

Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).

This skill should be used when the user wants to visualize data.

Zero-shot image classification and image-text search.

Use this skill when the user uploads Excel (.xlsx/.xls) or CSV files and wants to perform data analysis, generate statistics, create…

Use for creating publication-quality charts and multi-panel analysis summaries.

Build and run LLM-powered data processing pipelines with DocETL.

DSPy: declarative LM programs, auto-optimize prompts, RAG.

EAS service (paid). Use for anything related to EAS Observe - adding `expo-observe` to an Expo project (AppMetricsRoot/ObserveRoot HOC…