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All Skills

Total 50,367 skills, Data Processing has 2557 skills

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Showing 12 of 2557 skills

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Data Processinglkrdev/lookml_skills

lookml-refinements

Deep dive into LookML includes, refinements (layering), and project structure best practices. Essential for mastering Looker's object-oriented capabilities.

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4
Data Processinglkrdev/lookml_skills

lookml-explore

Use this skill when you need to create or modify a LookML Explore. This includes defining the Explore, joins, access grants, and basic configuration.

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4
Data Processingmembranedev/application-s...

ipinfoio

IPinfo.io integration. Manage Domains, ASNs, Companies. Use when the user wants to interact with IPinfo.io data.

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4
Data Processingruvnet/ruflo

market-ingest

Ingest and normalize market data into OHLCV vectors with HNSW indexing

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4
Data Processingmembranedev/application-s...

sportsdata

SportsData integration. Manage Teams, Leagues, Users. Use when the user wants to interact with SportsData data.

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4
Data Processingnimbleway/agent-skills

healthcare-providers-extract

Extracts structured practitioner data from healthcare practice websites. Returns names, credentials, specialties, contact info, and education for every provider on a practice's site. Use when user asks to extract, pull, or list doctors, providers, or staff from practice websites. Triggers: "extract doctors from", "pull providers from", "who are the providers at", "build a provider database", "list all doctors at", "scrape the team page", "get practitioner data from". Accepts practice URLs (pasted, CSV, Google Sheet) or discovers practices via Google Maps when given specialty + location. Single sites or 100+ URLs. Do NOT use for filling data gaps — use healthcare-providers-enrich instead. Do NOT use for credential validation — use healthcare-providers-verify instead. Do NOT use for discovering practices — use market-finder or local-places instead. Do NOT use for general extraction — use nimble-web-expert instead.

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4
Data Processingruvnet/ruflo

vector-hyperbolic

Embed hierarchical data in hyperbolic space via npx ruvector Poincare ball model, compute geodesic distances

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4
Data Processingexploreomni/omni-agent-sk...

omni-model-explorer

Discover and inspect Omni Analytics models, topics, views, fields, dimensions, measures, and relationships using the Omni CLI. Use this skill whenever someone wants to understand what data is available in Omni, explore their semantic model, find specific fields or views, check how tables join together, see what topics exist, or asks any variant of "what can I query", "what fields are available", "show me the model", "what data do we have", or "how is this data modeled". Also use when you need to understand the Omni model structure before building or modifying anything.

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4
Data Processingexploreomni/omni-agent-sk...

omni-query

Run queries against Omni Analytics' semantic layer using the Omni CLI, interpret results, and chain queries for multi-step analysis. Use this skill whenever someone wants to query data through Omni, run a report, get metrics, pull numbers, analyze data, ask "how many", "what's the trend", "show me the data", retrieve dashboard query results, or perform any data retrieval through Omni's query engine. Also use when someone wants to programmatically extract data from an existing Omni dashboard or workbook.

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4
Data Processingaws/agent-toolkit-for-aws

querying-data-lake

Execute and manage Athena SQL queries across default and federated catalogs (Glue, S3 Tables, Redshift). Triggers on phrases like: query data, run SQL, athena query, analyze table, SQL query, workgroup status, profile table, query Redshift catalog, query S3 Tables. Do NOT use for finding specific data assets (use finding-data-lake-assets), full catalog audits (use exploring-data-catalog), importing data (use ingesting-into-data-lake).

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4
Data Processingaws/agent-toolkit-for-aws

connecting-to-data-source

Create and troubleshoot AWS Glue connections to JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS), Redshift, Snowflake, and BigQuery. Gathers connection hints from user, discovers existing connections and RDS/Redshift candidates, registers credentials in Secrets Manager or IAM DB auth, configures VPC, and tests. Triggers on: connect to database, set up Glue connection, register data source, connect to Snowflake/BigQuery/RDS, connection timeout, test connection, troubleshoot connection. Do NOT use for moving data (use ingesting-into-data-lake), creating tables (use creating-data-lake-table), queries (use querying-data-lake), catalog exploration (use exploring-data-catalog), or SaaS (Salesforce, ServiceNow, SAP, MongoDB, Kafka).

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4
Data Processingwarpdotdev/oz-skills

analysis-artifacts

Generate reproducible analysis artifacts — SQL queries, Python visualizations, and summary tables — as you work through a BigQuery data analysis. Use when asked to conduct a deep dive, exploratory analysis, or investigation that goes beyond a simple data lookup.

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