Use when invalid data causes failures deep in execution, requiring validation at multiple system layers - validates at every layer data passes through to make bugs structurally impossible
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
Extract and validate data from requests including JSON, forms, query parameters, and path parameters. Use for handling user input and API payloads.
SQL for data analysis with exploratory analysis, advanced aggregations, statistical functions, outlier detection, and business insights. 50+ real-world analytics queries.
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use...
Use when designing databases for data-heavy applications, making schema decisions for performance, choosing between normalization and denormalization, selecting storage/indexing strategies,...
Access and analyze comprehensive drug information from the DrugBank database including drug properties, interactions, targets, pathways, chemical structures, and pharmacology data. This skill...
Access and analyze comprehensive drug information from the DrugBank database including drug properties, interactions, targets, pathways, chemical structures, and pharmacology data. This skill...
Deep-dive data profiling for a specific table. Use when the user asks to profile a table, wants statistics about a dataset, asks about data quality, or needs to understand a table's structure and...
Token-Oriented Object Notation (TOON) format expert for 30-60% token savings on structured data. Auto-applies to arrays with 5+ items, tables, logs, API responses, database results. Supports...
Master data manipulation, analysis, and visualization with Pandas, NumPy, and Matplotlib
Use when implementing or debugging ANY network request, API call, or data fetching. Covers fetch API, axios, React Query, SWR, error handling, caching strategies, offline support.
Identify structurally duplicate logic (pipeline-spine duplication) across semantically distinct modules; produces a duplication map and safe extraction/refactor plan.
This skill should be used when building data processing pipelines with CocoIndex v1, a Python library for incremental data transformation. Use when the task involves processing files/data into...
Generate structured narrative text visualizations from data using T8 (Text) schema. Use when users want to create data interpretation reports, summaries, or structured articles with entity...
This skill should be used when users are building or refining their Gioia data structure, mentions 'Gioia', 'data structure', 'themes', 'concepts', 'dimensions', '1st-order', '2nd-order',...
SEO and AEO (Answer Engine Optimization) best practices including EEAT principles, structured data, and technical SEO. Use when implementing metadata, sitemaps, structured data, or optimizing...
Skip to content Search… All gists Back to GitHub Sign in Sign up Instantly share code, notes, and snippets. @giansalex giansalex/torrent-courses-download-list.md forked from M-Younus/torrent...
Comprehensive toolkit for developing with the CocoIndex library. Use when users need to create data transformation pipelines (flows), write custom functions, or operate flows via CLI or API....
When the user wants to add, fix, or optimize schema markup and structured data on their site. Also use when the user mentions "schema markup," "structured data," "JSON-LD," "rich snippets,"...