Dados e Análise

Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with

Expert guidance for distributed NoSQL databases (Cassandra, DynamoDB). Focuses on mental models, query-first modeling, single-table design, and avoiding hot partitions in high-scale systems.

Professional data visualization creation using D3.js with support for interactive charts, custom visualizations, animations, and responsive design. Use for: (1) Creating custom interactive charts, (2) Building dashboards, (3) Network/graph visualizations, (4) Geographic data mapping, (5) Time series analysis, (6) Real-time data visualization, (7) Complex multi-dimensional data displays

Write, optimize, and debug T-SQL queries for Microsoft SQL Server. Covers CTEs, window functions, PIVOT, MERGE, APPLY operators, execution plan analysis, indexing strategies, and stored procedures. Use when working with SQL Server, T-SQL scripts, .sql files, stored procedures, query optimization, or database performance tuning.

A skill for analyzing data using Python (pandas) and generating professional visualizations (matplotlib/seaborn).

Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data. Use when the user wants to set up, fix, or evaluate analytics tracking (GA4, GTM, product analytics, events, conversions, UTMs). This skill focuses on measurement strategy, signal quality, and validation— not just firing events.

Query NCBI Gene via E-utilities/Datasets API. Search by symbol/ID, retrieve gene info (RefSeqs, GO, locations, phenotypes), batch lookups, for gene annotation and functional analysis.

Automated LLM-driven hypothesis generation and testing on tabular datasets. Use when you want to systematically explore hypotheses about patterns in empirical data (e.g., deception detection, content analysis). Combines literature insights with data-driven hypothesis testing. For manual hypothesis formulation use hypothesis-generation; for creative ideation use scientific-brainstorming.

Reviews Godot TileMap implementation for known pitfalls. Triggers AFTER implementation, when code involves TileMapLayer, TileSet, TileSetAtlasSource, TileSetScenesCollectionSource, terrain painting, set_cell, erase_cell, get_cell_tile_data, collision polygons on tiles, or NavigationRegion2D with tile-based navigation. Do NOT use this skill for planning or teaching — only for post-implementation re

Running experiments out of the data warehouse instead of via dedicated experiment platforms. SQL-based assignment, exposure logging discipline, metric definitions in dbt models, statistical analysis in SQL or Python, variance reduction with CUPED, sequential testing, and the operational tradeoffs vs platforms like Statsig and Optimizely. Triggers on warehouse-native experimentation, run experiment

How to actually instrument product analytics correctly. Event taxonomy, property design, naming conventions, schema versioning, identity stitching, funnel design, retention cohorts, North Star metric selection, dashboard hygiene, instrumentation debt, and the failure modes that produce data nobody trusts. Triggers on product analytics setup, event taxonomy, tracking plan, instrumentation, schema v

Gera imagens de visualização molecular com qualidade de publicação usando PyMOL. Ativa quando o usuário menciona PyMOL, visualização molecular, renderização de proteínas, ou deseja criar imagens de estruturas biomoleculares como proteínas, ligantes e sítios de ligação.