benchling-integration

21.8k

davila7

Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.

data-engineer

18.0k

sickn33

Build scalable data pipelines, modern data warehouses, and real-time streaming architectures. Implements Apache Spark, dbt, Airflow, and cloud-native data platforms. Use PROACTIVELY for data pipeline design, analytics infrastructure, or modern data stack implementation.

benchling-integration

10.8k

K-Dense-AI

Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.

data-context-extractor

8.4k

anthropics

Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts. BOOTSTRAP MODE - Triggers: "Create a data context skill", "Set up data analysis for our warehouse", "Help me create a skill for our database", "Generate a data skill for [company]" → Discovers schemas, asks key questions, generates initial skill with reference files ITERATION MODE - Triggers: "Add context about [domain]", "The skill needs more info about [topic]", "Update the data skill with [metrics/tables/terminology]", "Improve the [domain] reference" → Loads existing skill, asks targeted questions, appends/updates reference files Use when data analysts want Claude to understand their company's specific data warehouse, terminology, metrics definitions, and common query patterns.

sql-queries

8.4k

anthropics

Write correct, performant SQL across all major data warehouse dialects (Snowflake, BigQuery, Databricks, PostgreSQL, etc.). Use when writing queries, optimizing slow SQL, translating between dialects, or building complex analytical queries with CTEs, window functions, or aggregations.

databricks-migration-deep-dive

1.5k

jeremylongshore

Execute comprehensive platform migrations to Databricks from legacy systems. Use when migrating from on-premises Hadoop, other cloud platforms, or legacy data warehouses to Databricks. Trigger with phrases like "migrate to databricks", "hadoop migration", "snowflake to databricks", "legacy migration", "data warehouse migration".

warehouse-slotting-optimizer

376

a5c-ai

Warehouse slotting and layout optimization skill for pick path minimization and space utilization.

slotting-optimization-engine

376

a5c-ai

AI-driven warehouse slotting skill to optimize product placement based on velocity, pick frequency, and operational efficiency

sql-query-optimizer

376

a5c-ai

Analyzes and optimizes SQL queries across different data warehouse platforms (Snowflake, BigQuery, Redshift, Databricks) with platform-specific recommendations.

labor-productivity-optimizer

376

a5c-ai

AI-powered workforce planning and task assignment skill to maximize warehouse labor efficiency

wave-planning-optimizer

376

a5c-ai

Automated wave planning and pick path optimization skill to maximize warehouse throughput and order accuracy

warehouse-simulation-modeler

376

a5c-ai

Discrete event simulation skill for warehouse design validation and capacity planning

architecting-data

296

ancoleman

Strategic guidance for designing modern data platforms, covering storage paradigms (data lake, warehouse, lakehouse), modeling approaches (dimensional, normalized, data vault, wide tables), data mesh principles, and medallion architecture patterns. Use when architecting data platforms, choosing between centralized vs decentralized patterns, selecting table formats (Iceberg, Delta Lake), or designing data governance frameworks.

analyzing-data

258

astronomer

Queries data warehouse and answers business questions about data. Handles questions requiring database/warehouse queries including "who uses X", "how many Y", "show me Z", "find customers", "what is the count", data lookups, metrics, trends, or SQL analysis.

answering-natural-language-questions-with-dbt

219

dbt-labs

Writes and executes SQL queries against the data warehouse using dbt's Semantic Layer or ad-hoc SQL to answer business questions. Use when a user asks about analytics, metrics, KPIs, or data (e.g., "What were total sales last quarter?", "Show me top customers by revenue"). NOT for validating, testing, or building dbt models during development.

qe-wms-testing-patterns

215

proffesor-for-testing

Warehouse Management System testing patterns for inventory operations, pick/pack/ship workflows, wave management, EDI X12/EDIFACT compliance, RF/barcode scanning, and WMS-ERP integration. Use when testing WMS platforms (Blue Yonder, Manhattan, SAP EWM).

wms-testing-patterns

215

proffesor-for-testing

Warehouse Management System testing patterns for inventory operations, pick/pack/ship workflows, wave management, EDI X12/EDIFACT compliance, RF/barcode scanning, and WMS-ERP integration. Use when testing WMS platforms (Blue Yonder, Manhattan, SAP EWM).

data-engineer

75

htlin222

Build ETL pipelines, data warehouses, and streaming architectures. Use for data pipeline design or analytics infrastructure.

finding-expensive-queries

55

AltimateAI

Finds and ranks expensive Snowflake queries by cost, time, or data scanned. Use when: (1) User asks to find slow, expensive, or problematic queries (2) Task mentions "query history", "top queries", "most expensive", or "slowest queries" (3) Analyzing warehouse costs or identifying optimization candidates (4) Finding queries that scan the most data or have the most spillage Returns ranked list of queries with metrics and optimization recommendations.

data-pipeline-engineer

43

curiositech

Expert data engineer for ETL/ELT pipelines, streaming, data warehousing. Activate on: data pipeline, ETL, ELT, data warehouse, Spark, Kafka, Airflow, dbt, data modeling, star schema, streaming data, batch processing, data quality. NOT for: API design (use api-architect), ML training (use ML skills), dashboards (use design skills).

bigquery

36

lanej

Use bigquery CLI (instead of `bq`) for all Google BigQuery and GCP data warehouse operations including SQL query execution, data ingestion (streaming insert, bulk load, JSONL/CSV/Parquet), data extraction/export, dataset/table management, cost estimation with dry-run, authentication with gcloud, data pipelines, ETL workflows, and MCP server integration for AI-assisted querying. Modern TypeScript/Bun implementation replacing the Python `bq` CLI with instant startup (~10ms vs ~500ms), automatic cost awareness with confirmation prompts, and native streaming support (JSONL). Handles both small-scale streaming inserts (<1000 rows) and large-scale bulk loading (>10MB files) from Cloud Storage.

Data Architecture

31

melodic-software

Use when designing data platforms, choosing between data lakes, lakehouses, and warehouses, or implementing data mesh patterns. Covers modern data architecture approaches.

Data Engineer

29

omer-metin

Data pipeline specialist for ETL design, data quality, CDC patterns, and batch/stream processing. Use when "data pipeline, etl, cdc, data quality, batch processing, stream processing, data transformation, data warehouse, data lake, data validation, data-engineering, etl, cdc, batch, streaming, data-quality, dbt, airflow, dagster, data-pipeline, ml-memory" mentioned.

dbt-performance

28

sfc-gh-dflippo

Optimizing dbt and Snowflake performance through materialization choices, clustering keys, warehouse sizing, and query optimization. Use this skill when addressing slow model builds, optimizing query performance, sizing warehouses, implementing clustering strategies, or troubleshooting performance issues.

benchling-integration

26

lifangda

Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.

dbt

24

bbrewington

Use when building dbt models, adding tests, or designing data models. Covers dimensional modeling, model organization (staging/intermediate/marts), testing patterns, and warehouse-specific configurations.

kargo-skill

20

julianobarbosa

Comprehensive Kargo GitOps continuous-promotion platform skill. Use when implementing progressive delivery pipelines, promotion workflows, Freight management, ArgoCD integration, Warehouse configuration, stage pipelines, verification templates, or any Kargo-related tasks. Covers installation, core concepts, patterns, security, and complete YAML examples.

fabric-onelake-2025

19

JosiahSiegel

Microsoft Fabric Lakehouse, OneLake, and Fabric Warehouse connectors for Azure Data Factory (2025)

benchling-integration

15

oimiragieo

Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.

dbt

9

TerminalSkills

dbt (data build tool) transforms data in your warehouse using SQL SELECT statements. Learn project setup, models, tests, documentation, incremental materializations, and integration with data warehouses like PostgreSQL, BigQuery, and Snowflake.

data-engineering

7

louloulin

Expert in data pipeline design, ETL/ELT processes, data warehousing, and big data technologies

wms-react-components

6

Rytass

WMS map React components. Use when building warehouse map editors, interactive floor plans, location visualization, or spatial management interfaces. Based on ReactFlow/XYFlow. Keywords: WMS, warehouse map, floor plan, ReactFlow, XYFlow, map editing, spatial, location

wms-module

6

Rytass

WMS NestJS module. Use when working with warehouse management, inventory tracking, location management, stock transactions, batch management, or warehouse maps. Implements LocationService, MaterialService, StockService, OrderService, and WarehouseMapService. Keywords: WMS, warehouse, warehousing, inventory, location, TypeORM, NestJS, batch, stock

multi-source-data-conflation

5

sunnypatneedi

Merge and reconcile data from multiple sources into a unified view. Use when integrating APIs, consolidating databases, building data warehouses, or creating master data. Covers entity resolution, conflict resolution, data quality, and real-time vs batch conflation.

data-engineer

5

agent-skills-hub

Build scalable data pipelines, modern data warehouses, and real-time streaming architectures. Implements Apache Spark, dbt, Airflow, and cloud-native data platforms. Use PROACTIVELY for data pipeline design, analytics infrastructure, or modern data stack implementation.

data-pipelines

5

ZLStas

Apply Data Pipelines Pocket Reference practices (James Densmore). Covers Infrastructure (Ch 1-2: warehouses, lakes, cloud), Patterns (Ch 3: ETL, ELT, CDC), DB Ingestion (Ch 4: MySQL, PostgreSQL, MongoDB, full/incremental), File Ingestion (Ch 5: CSV, JSON, cloud storage), API Ingestion (Ch 6: REST, pagination, rate limiting), Streaming (Ch 7: Kafka, Kinesis, event-driven), Storage (Ch 8: Redshift, BigQuery, Snowflake), Transforms (Ch 9: SQL, Python, dbt), Validation (Ch 10: Great Expectations, schema checks), Orchestration (Ch 11: Airflow, DAGs, scheduling), Monitoring (Ch 12: SLAs, alerting), Best Practices (Ch 13: idempotency, backfilling, error handling). Trigger on "data pipeline", "ETL", "ELT", "data ingestion", "Airflow", "dbt", "data warehouse", "Kafka streaming", "CDC", "data orchestration".

data-pipelines

5

booklib-ai

Apply Data Pipelines Pocket Reference practices (James Densmore). Covers Infrastructure (Ch 1-2: warehouses, lakes, cloud), Patterns (Ch 3: ETL, ELT, CDC), DB Ingestion (Ch 4: MySQL, PostgreSQL, MongoDB, full/incremental), File Ingestion (Ch 5: CSV, JSON, cloud storage), API Ingestion (Ch 6: REST, pagination, rate limiting), Streaming (Ch 7: Kafka, Kinesis, event-driven), Storage (Ch 8: Redshift, BigQuery, Snowflake), Transforms (Ch 9: SQL, Python, dbt), Validation (Ch 10: Great Expectations, schema checks), Orchestration (Ch 11: Airflow, DAGs, scheduling), Monitoring (Ch 12: SLAs, alerting), Best Practices (Ch 13: idempotency, backfilling, error handling). Trigger on "data pipeline", "ETL", "ELT", "data ingestion", "Airflow", "dbt", "data warehouse", "Kafka streaming", "CDC", "data orchestration".

dts-postgres

4

tekliner

Query DTS PostgreSQL via Redash API for marketing data warehouse. Use when user says "DTS Postgres", "Redash query", "marketing warehouse", "funnel analysis".

babylonjs

2

Curiosity-Ai-BV

Babylon.js 8 3D engine development expertise with curated API patterns, code examples, and on-demand documentation access. Use when working with Babylon.js scenes, meshes, materials (PBR/Standard), cameras, lights, shadows, GUI (2D/3D), animations, physics (Havok), thin instances, glTF loading, post-processing, WebXR, or any 3D rendering task. Covers: (1) Scene setup and engine initialization (WebGL/WebGPU), (2) Mesh creation, transforms, instancing, and merging, (3) PBR and Standard materials with textures, (4) Camera types (ArcRotate, Universal, Follow), (5) Lighting and shadows, (6) 2D/3D GUI with AdvancedDynamicTexture, (7) Animation system and animation groups, (8) Asset loading (glTF, OBJ, STL), (9) Performance optimization and profiling, (10) ASRS/warehouse digital twin visualization patterns.

Location Advisor

2

huangqianqian120

A site-selection advisory system. Based on McKinsey methodology, it uses MECE factor decomposition, data-driven scoring, and hypothesis validation to support site selection decisions for retail stores, restaurants, warehouses, factories, offices, and more. Supports API integration and local fallback.

ai-data-integration

1

dtsong

Use this skill when connecting AI or LLMs to data platforms. Covers MCP servers for warehouses, natural-language-to-SQL, embeddings for data discovery, LLM-powered enrichment, and AI agent data access patterns. Common phrases: "text-to-SQL", "MCP server for Snowflake", "LLM data enrichment", "AI agent access". Do NOT use for general data integration (use data-integration) or dbt modeling (use dbt-transforms).

benchling-integration

1

iamseungpil

Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.

dbt-skill

1

dtsong

Use when working with dbt (data build tool) - creating models, writing tests, CI/CD pipelines, materializations, sources, staging/intermediate/marts layers, Snowflake/BigQuery warehouse configuration, incremental strategies, Jinja macros, data quality, semantic layer, or making analytics engineering decisions

Benchling Integration

reikiplanet

Integration with Benchling’s R&D platform. Programmatic access to registry (DNA, RNA, proteins), inventory, electronic lab notebook (ELN) entries, and workflows via API. Build Benchling Apps, query the Benchling Data Warehouse for analytics, and automate lab data management and integrations.

Databricks Migration Deep Dive

nivkazdan

Execute comprehensive platform migrations to Databricks from legacy systems. Use when migrating from on-premises Hadoop, other cloud platforms, or legacy data warehouses to Databricks. Trigger with phrases like "migrate to databricks", "hadoop migration", "snowflake to databricks", "legacy migration", "data warehouse migration".

Snowflake Automation

reikiplanet

Automate Snowflake data warehouse operations -- list databases, schemas, and tables, execute SQL statements, and manage data workflows via the Composio MCP integration.

build-supaflow-connector

supaflow-labs

Build or review Supaflow connectors using a phased workflow for source connectors, warehouse destinations, and activation targets. Use this skill when implementing new connectors, debugging connector behavior, or validating connector quality in a Supaflow platform repository with gate checks and anti-pattern enforcement.

Warehouse Layout Planner

Eli-yu-first

Design optimal warehouse layouts with pick path optimization and storage allocation