Skill UI

Guides on using SwanLab for open-source ML experiment tracking, offering local or self-hosted dashboards, rich media logging, and integrations with PyTorch, Transformers, Lightning, or Fastai for comparing runs and monitoring metrics.

ADHX provides a dedicated API to fetch X/Twitter posts as clean, structured JSON. It extracts comprehensive data, including author profiles, engagement metrics (likes, retweets), and full article content for long-form posts. This method is vastly superior to traditional scraping techniques, making it ideal for LLM analysis, summarization, and structured data workflows.

Trackio is a comprehensive library for logging, visualizing, and managing ML experiment metrics and alerts. It allows developers to use a Python API to log metrics and set diagnostic alerts (INFO/WARN/ERROR) during training. Furthermore, a dedicated CLI enables metric retrieval and dashboard viewing, syncing data to Hugging Face Spaces for persistent, remote monitoring, making it ideal for autonomous ML agent workflows.

Guides researchers through a post-experiment gate that collects metrics, submits them to Codex for verdicts, and routes follow-up actions based on whether the intended claim is supported, partially supported, or refuted.

Generates a single formula-driven Excel dashboard from CSV/tabular data, complete with KPI cards, charts, sparklines, and conditional formatting so analysts can instantly review metrics and share an executive-ready .xlsx output.

OpenSearch is a distributed search and analytics engine integrated into KubeSphere's WizTelemetry Observability Platform. It is designed to efficiently store, index, and analyze vast amounts of observability data, including Kubernetes logs, auditing events, system metrics, and application notifications. Used for building comprehensive monitoring dashboards and deep operational insights.

End-to-end Neuropixels recording analysis covering SpikeGLX/OpenEphys/NWB loading, preprocessing, motion correction, Kilosort4 sorting, quality metrics, Allen/IBL curation, and AI-assisted visualization for extracellular electrophysiology.

scikit-bio provides a Python-native biological data toolkit for reading/writing FASTA/Newick files, manipulating sequences, building alignments and phylogenies, and calculating diversity metrics for microbiome and ecology workflows.

Toolkit for Python-based survival and time-to-event modeling with scikit-survival, supporting Cox models, ensemble learners, SVMs, and evaluation metrics for censored data.

Statsmodels is a comprehensive Python library dedicated to advanced statistical modeling and econometrics. It provides tools for rigorous statistical inference, including Ordinary Least Squares (OLS), Generalized Linear Models (GLM), mixed-effects models, and time series analysis (ARIMA). Use this skill for detailed diagnostics, coefficient estimation, hypothesis testing, and producing publication-ready statistical reports in fields like econometrics and biostatistics.

Provides open REST access to the U.S. Treasury Fiscal Data API so analysts can pull national debt, spending, revenue, interest rates, exchange rates, auctions, and savings bond statistics without an API key; useful for financial dashboards, debt tracking, and research involving federal fiscal metrics.

A comprehensive workflow designed to build deep revenue analytics dashboards using exported Clari data. It calculates key metrics such as forecast accuracy, pipeline coverage ratios, and tracks representative performance changes. Ideal for financial analysts and sales managers needing to assess revenue health and forecast reliability.