Data Analysis Agent Skills

Tracks institutional investor ownership changes and portfolio flows using 13F filings data to identify stocks with significant smart money accumulation or distribution.

Monitor dividend portfolios for risk triggers and route anomalies into a human review queue without auto-selling.

Screens for dividend growth stocks with 12%+ annual dividend growth and 1.5%+ yield that are experiencing temporary pullbacks identified by RSI oversold conditions (RSI ≤40).

Add EAS Observe to an Expo project for startup, navigation, and custom-event performance metrics, query them via the EAS CLI, and interpret the results.

Analyze PCAP files by reconstructing TCP/UDP sessions, decoding application-layer protocols, and correlating packet sequences with host or malware behavior for CTF challenges.

End-to-end Kaggle competition workflow for scored submissions, covering code competitions, validation, metrics, public notebook/discussion intel, tabular/text/image modeling, tuning, ensembling, multi-notebook architectures, Kaggle GPU offload, and hidden-test debugging.

Provides scikit-learn compatible algorithms for time series machine learning, including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search.

Streams live training metrics, system stats, and gradients from active W&B runs, alerts on metric regressions, and posts summaries to Slack.

Fetches current weather and forecasts for any location using free, keyless APIs like wttr.in and Open-Meteo.

Calculates polygenic risk scores from 23andMe or AncestryDNA genotype files using PGS Catalog scoring files, then estimates population percentiles and risk categories.

Fetches your latest WHOOP recovery, sleep, and strain data and generates a short set of daily suggestions.

Process and analyze tabular datasets larger than RAM using lazy, out-of-core DataFrames, with fast aggregations, visualization, and machine learning integration.

Parse FCS (Flow Cytometry Standard) files v2.0-3.1, extracting events as NumPy arrays, metadata, and channel information, with support for creating and modifying FCS files.

High-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.

Queries the 1000 Genomes Project dataset (3,202 whole-genome-sequenced individuals, GRCh38) at the level of individual participants, returning variants, carriers, and relatedness with allele frequencies and annotations.

Reviews a video rough cut by generating deterministic metrics, critiquing the edit against brief and blueprint, and producing review_report.yaml and review_patch.json artifacts.

Define el enfoque, las herramientas y el pipeline de análisis antes de escribir código, eligiendo entre SQL, Python o un enfoque híbrido según la pregunta y los datos.

Lee y escribe datos en múltiples formatos con Pandas — CSV, Excel, Parquet, JSON, Feather — y elige el formato óptimo según el caso.

Analiza datasets con Pandas y NumPy: explora distribuciones, correlaciones y patrones, y aplica tests de hipótesis para extraer conocimiento no obvio.

Guides creating clean, reproducible Jupyter notebooks with structured workflows, best practices, and IPython magic for analysis and presentation.

Search SAM.gov for contract opportunities and registered entities, and query USASpending.gov for federal award data.

Queries CDC open data and WHO Global Health Observatory indicators for public health intelligence, covering disease surveillance, vaccinations, and mortality.

Guides database design, implementation, optimization, migration, pipeline development, and operations across SQL and NoSQL platforms.

Create, manipulate, and analyze complex networks and graphs with the NetworkX Python package, covering graph construction, algorithms, generators, I/O, and visualization.

Queries EVM blockchain data across 8 chains with USD pricing, including wallet portfolios, token info, transactions, gas, and contract inspection.

Query Google Analytics 4 (GA4) data via the Analytics Data API. Use when you need to pull website analytics like top pages, traffic sources, user counts, sessions, conversions, or any GA4 metrics/dimensions. Supports custom date ranges and filtering.

Manage Loom video recordings via the Loom API, including listing, retrieving details and transcripts, updating, deleting, and fetching analytics.

Reads, extracts, merges, splits, rotates, watermarks, creates, encrypts, and OCRs PDF files using Python libraries and command-line tools.

Provides data-driven endurance cycling coaching using Intervals.icu data, including fitness assessment, workout planning, and power curve analysis.

Queries the DriftaBot Registry to check for API spec drifts, breaking changes, and provider information across 59+ API providers.

Runs SQL queries and data conversions on CSV, Parquet, and JSON files using the DuckDB command-line interface, including schema inspection and output formatting.

Create, analyze, and visualize complex networks and graphs in Python using NetworkX, including graph construction, algorithms, generators, I/O, and plotting.

Perform fast genomic interval operations (overlap, nearest, merge, coverage, cluster, complement, subtract, count-overlaps), multi-format bioinformatics I/O, DataFusion SQL, and pileup on Polars DataFrames via the polars-bio library, serving as a scalable alternative to bioframe and bedtools.

Queries 9 genomic databases in parallel for a given rsID, returning unified GWAS, PheWAS, eQTL, and fine-mapping reports.

Discovers and executes bioinformatics tools from the Galaxy ecosystem via natural language, with multi-signal scoring, workflow templates, and reproducibility bundles.

Performs differential expression analysis on label-free quantitative (LFQ) proteomics data from MaxQuant and DIA-NN outputs, including preprocessing, imputation, statistical testing, and visualization.