Results for “data”

Performs comprehensive SQL code review across all major databases, analyzing security, performance, maintainability, and anti-patterns.

Automate spreadsheet operations including creating workbooks, writing data, formatting cells, upserting rows, and managing worksheets across Microsoft Excel and Google Sheets.

Automate Bitquery blockchain data queries through Composio's Bitquery toolkit via Rube MCP, with dynamic tool discovery and connection management.

Perform numerical computing, matrix operations, data analysis, and scientific visualization using MATLAB or GNU Octave.

Query the Precision Medicine Knowledge Graph (PrimeKG) for multiscale biological data including genes, drugs, diseases, phenotypes, and more.

Compresses long K-line (candlestick) data into a fixed-length sequence using OHLC aggregation rules and applies min-max normalization.

Filters and prioritizes compound libraries in drug discovery using drug-likeness rules, structural alerts, complexity metrics, and a query language.

Perform astronomical research and data analysis with coordinate transformations, unit conversions, FITS file handling, cosmological calculations, time handling, and table operations.

Provides reference documentation and code patterns for using Biopython to handle biological sequences, file formats, database access, alignments, structures, and phylogenetics.

Recalibrates conservative Kiro cache-estimation coefficients from recent successful usage samples, producing a recommendation for manual admin Kmodel updates.

Analyze single-cell RNA-seq data with Scanpy, covering quality control, normalization, dimensionality reduction, clustering, marker gene identification, and visualization.

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

Analyze single-cell RNA-seq data with Scanpy, covering quality control, normalization, clustering, marker gene identification, visualization, and trajectory analysis.

Computes bibliometric indices for AI/NLP conferences, including QQE, average/median citations, and citation inequality, from annual publication and citation data.

Dask parallel computing reference for Python. Covers Dask DataFrame (parallel Pandas), Dask Array (parallel NumPy), Dask Delayed for custom parallelism, Dask Bag, distributed clusters, dashboard monitoring, and scaling best practices.

Use for writing, reviewing, debugging, testing, or optimizing Python code that embeds DuckDB, executes analytical SQL, manages DuckDB connections and transactions, builds DuckDB relations, queries Parquet/CSV/Arrow/pandas/Polars inputs, or exports query results. Trigger on connection scope, parameters, replacement scans, materialization, concurrency, extensions, and query plans. Do not use for generic SQL with another engine, DuckDB CLI-only work, server-database administration, dbt-only projects, or dataframe work that does not call DuckDB.

Prisma ORM for Node.js/TypeScript. Covers schema definition, migrations, and type-safe queries. Use when working with Prisma. USE WHEN: user mentions "prisma", "schema.prisma", "prisma migrate", "prisma generate", "prisma studio", "@prisma/client", asks about "how to define models in prisma", "prisma relations", "prisma transactions", "type-safe database queries" DO NOT USE FOR: raw SQL queries - use `database-query` MCP; Drizzle ORM - use `drizzle` skill; TypeORM - use `typeorm` skill; SQLAlchemy - use `sqlalchemy` skill

Drizzle ORM for TypeScript. Covers schema definition, queries, and migrations. Use for type-safe SQL with minimal overhead. USE WHEN: user mentions "drizzle", "drizzle-orm", "drizzle-kit", "pgTable", "mysqlTable", asks about "lightweight orm", "sql-like orm", "drizzle schema", "drizzle migrations", "drizzle studio", "type-safe sql builder" DO NOT USE FOR: Prisma projects - use `prisma` skill; TypeORM - use `typeorm` skill; raw SQL - use `database-query` MCP; SQLAlchemy - use `sqlalchemy` skill; NoSQL databases - use `mongodb` skill

Translates natural language data intents into syntactically valid Perfetto SQL queries and executes them against a local trace file using trace_processor.

Design, build, and optimize Microsoft Fabric Lakehouse solutions with guidance on core concepts, components, security, shortcuts, and performance optimization.

Automate gender data lookups and name-based gender predictions using the Genderapi IO API through Rube MCP and Composio.

Extracts structured product listings from Amazon, including titles, ASINs, prices, ratings, and specifications, using the BrowserAct API.

Extract structured product launch data from Product Hunt leaderboards, enriched with maker profiles and website contact information.

Build and deploy bioinformatics workflows as serverless pipelines on the Latch platform using Python decorators, cloud data management, and GPU support.

Audit cross-platform attribution by reconciling conversion definitions, reporting windows, and data sources across browsers, servers, MMPs, and ad platforms.

Creates interactive, publication-quality charts with 40+ types, hover tooltips, zoom, and web-embeddable exports for dashboards and exploratory analysis.

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

Scans local repositories and a Supabase database to inventory all pathway, portal, and theme content, producing a categorized report organized by portal.

Queries the Metabolomics Workbench REST API to retrieve metabolite, study, and RefMet data in JSON or text formats.

Analise arquivos FCS (Flow Cytometry Standard) v2.0-3.1. Extraia eventos como arrays NumPy, leia metadados/canais, converta para CSV/DataFrame, para pré-processamento de dados de citometria de fluxo.

Analyze sprint data with Python scripts for velocity forecasting, health scoring, and retrospective insights to coach agile teams.

Set up, audit, and debug analytics tracking implementations including GA4, Google Tag Manager, event taxonomy, and conversion tracking.

Defines vehicle routing problem types (TSP, VRP, PDP) and the data requirements needed to formulate them, without covering any API or interface details.

Quickly query genomic reference databases for Ensembl IDs, gene metadata, sequences, BLAST searches, and enrichment analysis using the gget CLI or Python package.

Generates a compact HTML KPI digest from Adobe Analytics, showing how key metrics changed over a period and what drove the movement.

Build and run evaluators for AI/LLM applications using Phoenix, covering error analysis, custom evaluators, experiments, and production monitoring.