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Found 372 Skills
Production-ready microscopy image analysis and quantitative imaging data skill for colony morphometry, cell counting, fluorescence quantification, and statistical analysis of imaging-derived measurements. Processes ImageJ/CellProfiler output (area, circularity, intensity, cell counts), performs Dunnett's test, Cohen's d effect size, power analysis, Shapiro-Wilk normality tests, two-way ANOVA, polynomial regression, natural spline regression with confidence intervals, and comparative morphometry. Supports CSV/TSV measurement tables, multi-channel fluorescence data, colony swarming assays, and neuron counting datasets. Use when analyzing microscopy measurement data, colony area/circularity, cell count statistics, swarming assays, co-culture ratio optimization, or answering questions about imaging-derived quantitative data.
Implements efficient API pagination using offset, cursor, and keyset strategies for large datasets. Use when building paginated endpoints, implementing infinite scroll, or optimizing database queries for collections.
Detects and redacts Personally Identifiable Information (PII) like emails, phone numbers, and credit cards. Use when cleaning logs, datasets, or communications to comply with GDPR/CCPA privacy standards.
Resolves shared ecosystem environment constants (HuggingFace credentials, dataset repo IDs, project root path) for any plugin without depending on internal shared libraries. V2 enforces Token Leakage constraints.
Implements Syncfusion WinUI Cartesian Charts (SfCartesianChart) for data visualization in WinUI applications. Use this when working with column, line, bar, area, or financial charts (OHLC, Candle). This skill covers axis configuration, legends, tooltips, zooming/panning, data labels, and high-performance fast series for large datasets.
Hugging Face integration. Manage Models, Datasets, Spaces. Use when the user wants to interact with Hugging Face data.
Research TikTok Creative Center or ad-library style datasets for winning ad patterns, regions, objectives, hook language, and creative signals without mixing paid ads with organic creator discovery.
Build creator lead lists for TikTok, Instagram, and X by turning normalized platform datasets into outreach-ready leads with contact signals, shortlist logic, and draft outreach messages. Use this when the user wants creator discovery, contact extraction, shortlist building, or outreach prep.
Nasdaq Data Link integration. Manage Datasets. Use when the user wants to interact with Nasdaq Data Link data.
Audit datasets for completeness, consistency, accuracy, and validity. Profile data distributions, detect anomalies and outliers, surface structural issues, and produce an actionable remediation plan.
Resolve data lake and lakehouse asset references across Glue Data Catalog, S3, S3 Tables, and Redshift. Triggers on: find the table, where is our data, which table has, locate dataset, find data for, search catalog, what tables match, Redshift table, lakehouse table, data lake table, warehouse table, reverse lookup S3 path. Do NOT use for: full catalog audits (use exploring-data-catalog), running queries (use querying-data-lake), creating tables (use creating-data-lake-table).
Import datasets from HuggingFace and convert them to Coval test sets. Use when the user wants to create test cases from HuggingFace dataset or repository.