Results for “data-fields”

You are a data triager that answers data questions by routing them across a network of skills and agents. These questions may involve pulling data from a Snowflake warehouse, computing metrics, locating relevant tables or fields, diagnosing a metric change, or performing exploratory analysis. Your job is to determine how to answer a question and which skills and subagents to invoke.

Use this skill to write and run SQL queries, pull data, build metrics, or answer analytical questions. Always use this skill when you need to query data.

Use this skill to write and run SQL queries, pull data, build metrics, or answer analytical questions. Always use this skill when you need to query data.

Use this skill for any data or analytics task — querying databases, analyzing metrics, exploring data warehouses, processing datasets, or creating visualizations.

Use this skill for any data or analytics task — querying databases, analyzing metrics, exploring data warehouses, processing datasets, or creating visualizations.

Fetch dataset metadata, paginate rows, search text, apply filters, and download parquet URLs from the Hugging Face Dataset Viewer API.

Build synthetic datasets and data generation pipelines using the Data Designer library.

Bulk-migrate repo labels and Project V2 fields into GitHub org-level issue fields (single select, text, number, date).

Limpia y transforma texto en DataFrames usando expresiones regulares: extrae emails, teléfonos, fechas y precios, valida formatos como CUIL o CBU, y maneja datos inconsistentes con opciones de fuzzy matching.

Query the Clever Data API to retrieve information about contacts, districts, schools, sections, students, and teachers across 44 read-only endpoints.

Generate realistic dummy datasets for testing with customizable columns, constraints, and output formats (CSV, JSON, SQL, Python script).

Provides safe, reversible database schema change patterns for PostgreSQL, MySQL, and common ORMs, with guidance on zero-downtime deployments, rollbacks, and migration tooling.

Your data-fill agent. Connect a contact-enrichment tool (contact-level) or a company-enrichment tool (company-level), or both for the full waterfall, to fill gaps on any list. Given a name plus a company, find email, phone, LinkedIn, and title. Given a domain, find headcount, funding, technographic profile, and hiring intent. Trigger on "enrich these contacts with emails", "find LinkedIn URLs for {list}", "get phone numbers for {contacts}", "who are the decision makers at {company}", "complete this prospect list", "enrich this CSV", "get the technographic stack for {company}", "fill in missing data on {list}", or any data-completion, list-enrichment, or contact-lookup question.

Designs and implements big data architectures, processes large-scale datasets with distributed systems, and optimizes data pipelines for throughput using Hadoop, Spark, and cloud platforms.

Converts CSV, Excel, or JSON data into a polished, interactive visual report page with KPI cards, charts, data tables, and insights.

Data analysis best practices with pandas, numpy, matplotlib, seaborn, and Jupyter notebooks.

Use this skill when the user uploads Excel (.xlsx/.xls) or CSV files and wants to perform data analysis, generate statistics, create summaries, pivot tables, SQL queries, or any form of structured data exploration. Supports multi-sheet Excel workbooks, aggregation, filtering, joins, and exporting results to CSV/JSON/Markdown.

Expert database architect specializing in data layer design from scratch, technology selection, schema modeling, and scalable database architectures. Masters SQL/NoSQL/TimeSeries database selection, normalization strategies, migration planning, and performance-first design. Handles both greenfield architectures and re-architecture of existing systems. Use PROACTIVELY for database architecture, technology selection, or data modeling decisions.

Administra bases de datos PostgreSQL, MySQL, Redis y SQLite: diseña esquemas, optimiza queries, configura migraciones, replicación y backups.

DataFrame operations with pandas and polars — groupby, joins, reshaping, performance. Use when manipulating tabular data, choosing between pandas and polars, optimizing DataFrame code, or translating between the two libraries.

Analyze datasets to answer defined questions through statistical methods, trend identification, hypothesis testing, and correlation analysis. Use when the user needs evidence-backed findings or decisions from data; use exploratory-data-analysis instead for open-ended first-pass profiling before questions are defined.

You are a data triager that answers data questions by routing them across a network of skills and agents. These questions may involve pulling data from a Snowflake warehouse, computing metrics, locating relevant tables or fields, diagnosing a metric change, or performing exploratory analysis. Your job is to determine how to answer a question and which skills and subagents to invoke.

Analyzes uploaded data files with full Python access, producing cleaned datasets, statistical reports, charts, and dashboards via the CellCog coding agent.

GDPR and CCPA/CPRA privacy compliance audit for codebases. Inventories PII fields (email, phone, SSN, IP, device ID, geolocation, biometrics, behavioral data), maps data collection points (forms, APIs, cookies, analytics, error tracking), audits consent mechanisms (cookie banners, opt-in, pre-checked boxes, consent withdrawal), verifies data subject rights implementation (right to access, erasure, rectification, portability, opt-out, Do Not Sell), traces third-party data sharing (Google Analytics, Facebook Pixel, Stripe, SendGrid, Sentry), and checks data retention policies and automated purging. Use when auditing privacy compliance, building data export or deletion endpoints, reviewing cookie consent, or assessing DSAR readiness.