250 free skills · page 2 of 5
Data Engineering skills
Skills for data engineering — ETL pipelines, Airflow DAGs, Spark jobs, and data warehouse modeling.
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spark-recipe-calendar-auditreaddle/spark-cli-skillsAnalyze meeting load over a week or custom time range. Count meetings, estimate total hours, identify the busiest days, flag back-to-back chains, and surface free blocks.Data Engineering174spark-recipe-stakeholder-briefreaddle/spark-cli-skillsGiven a person's name, compile all recent interactions — meetings and emails — into a relationship brief. Useful before 1:1s, performance reviews, or re-engaging with someone after a gap.Data Engineering171
data-engineerdaffy0208/ai-dev-standardsExpert in data pipelines, ETL processes, and data infrastructureData Engineering171spark-persona-exec-assistantreaddle/spark-cli-skillsYou are an executive assistant managing the user's email, calendar, and contacts through Spark. Your goal is to keep the user informed, organized, and responsive.Data Engineering171
data-engineeringrohitg00/awesome-claude-code-toolkitData engineering patterns for ETL pipelines, data warehousing, Apache Spark, and data quality validationData Engineering170spark-recipe-topic-timelinereaddle/spark-cli-skillsFor a given project or topic, build a unified chronological narrative by interleaving meeting discussions and email threads. Useful for catching up, briefing someone new, or preparing a status update.Data Engineering170
alibabacloud-emr-spark-managealiyun/alibabacloud-aiops-skillsManage EMR Serverless Spark workspaces through Alibaba Cloud API. You are a Spark-savvy data engineer who not only knows how to call APIs, but also knows when to call them and what parameters to use.Data Engineering169spark-recipe-newsletter-cleanupreaddle/spark-cli-skillsAudit and prune newsletter subscriptions. Block the unwanted, unsubscribe from the noisy, and enable AI summaries for the ones worth keeping.Data Engineering167
teneroaibtcdev/skillsTenero (formerly STXTools) market analytics — token info, market stats, top gainers/losers, wallet holdings and trades, trending DEX pools, whale trades, holder distribution, and search. Covers Stacks, Spark, and SportsFun chains. No API key required.Data Engineering167spark-recipe-inbox-zeroreaddle/spark-cli-skillsProcess the inbox to zero using category-first triage. Work through categories in priority order, then take action on each email.Data Engineering166spark-recipe-shared-inbox-statusreaddle/spark-cli-skillsReview the health of one or more shared inboxes - open items, completed work, unassigned emails, and how assignments are distributed across team members.Data Engineering166
airflow-expertpersonamanagmentlayer/pclExpert-level Apache Airflow orchestration, DAGs, operators, sensors, XComs, task dependencies, and schedulingData Engineering166spark-recipe-invitation-managerreaddle/spark-cli-skillsProcess pending calendar invitations by checking availability for each and presenting a decision list with recommendations.Data Engineering163spark-recipe-schedule-meetingreaddle/spark-cli-skillsFind mutual availability with attendees and present time slot options for scheduling.Data Engineering162
python-pipelinejamditis/claude-skills-journalismPython data pipelines with modular architecture. Use for content workflows, batch jobs, or Google Sheets/Drive integration.Data Engineering157aibtc-agentsaibtcdev/skillsCommunity registry of agent configurations for the AIBTC platform — browse reference configs for arc0btc, spark0btc, iris0btc, loom0btc, and forge0btc, or copy the template to bootstrap a new agent.Data Engineering157spark-recipe-label-organizereaddle/spark-cli-skillsOrganize emails using labels and folders. Attach project labels, detach incorrect ones, and move misfiled emails to the right location.Data Engineering155spark-recipe-team-workloadreaddle/spark-cli-skillsDeep audit of how work is distributed across a team. Surfaces per-member assignment loads, items you've delegated, unassigned work, and imbalances.Data Engineering153spark-recipe-priority-tuningreaddle/spark-cli-skillsFine-tune who gets auto-prioritized by reviewing the current priority category and adjusting contact-level settings.Data Engineering151
data-warehouse-experimentationrampstackco/claude-skillsRunning 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 experiments in BigQuery, run experiments in Snowflake, dbt experiments, SQL t-test, CUPED variance reduction, exposure log, sample ratio mismatch, sequential testing, mSPRT, doubly robust estimation, build vs buy experimentation. Also triggers when the team is choosing between platform and warehouse, building warehouse-native experiment infrastructure, auditing one, or running an experiment with a custom metric the platform cannot handle.Data Engineering151spark-recipe-notification-hygienereaddle/spark-cli-skillsTame notification overload by identifying noisy senders, reclassifying misplaced mail, grouping repetitive notifications, and clearing out what's no longer relevant.Data Engineering150spark-persona-founderreaddle/spark-cli-skillsYou are a founder / CEO managing a high-volume inbox through Spark. Your goal is to stay on top of what matters, delegate aggressively, and never let email become a bottleneck.Data Engineering149spark-recipe-draft-batchreaddle/spark-cli-skillsReview and finalize multiple pending drafts in a single session. Read context for each, decide whether to edit, keep, or discard.Data Engineering147spark-recipe-new-sender-reviewreaddle/spark-cli-skillsProcess Spark's GateKeeper queue of new senders. Review each, accept legitimate contacts, and block unwanted ones.Data Engineering147spark-persona-freelancerreaddle/spark-cli-skillsYou are a freelancer / solo operator managing multiple clients through Spark. Your goal is to keep response times low, track client work separately, and ensure invoices get paid.Data Engineering144spark-recipe-vacation-catchupreaddle/spark-cli-skillsProcess a large email backlog after vacation or extended absence. Prioritize ruthlessly, batch-archive noise, and surface only what truly needs attention.Data Engineering144spark-recipe-delegate-and-trackreaddle/spark-cli-skillsAssign emails to teammates with context, set due dates, and track delegation status to completion.Data Engineering143spark-persona-project-managerreaddle/spark-cli-skillsYou are a project manager tracking deliverables, stakeholder communications, and cross-team coordination through Spark. Your goal is to keep projects on track by ensuring nothing falls through the cracks and everyone stays aligned.Data Engineering143spark-persona-meeting-managerreaddle/spark-cli-skillsYou are a meeting manager handling preparation, follow-ups, and scheduling through Spark. Your goal is to ensure the user goes into meetings prepared and follows up on action items afterward.Data Engineering142spark-recipe-meeting-followupreaddle/spark-cli-skillsReview a meeting transcript, extract action items, and draft follow-up emails to attendees.Data Engineering142
databricks-execution-computedatabricks/databricks-agent-skillsExecute code and manage compute on Databricks: run Python/Scala/SQL/R via serverless, classic, or interactive clusters, and create/resize/delete clusters and SQL warehouses.Data Engineering142
segmentmembranedev/application-skillsSegment is a customer data platform that helps businesses collect, clean, and control their customer data. It's used by marketing, product, and engineering teams to understand user behavior and personalize experiences. They can then send this data to various marketing and analytics tools.Data Engineering141spark-recipe-shared-inbox-triagereaddle/spark-cli-skillsProcess open items in shared inboxes. Review each item, assign to the right person, respond where possible, and mark resolved items as done.Data Engineering140databricks-spark-structured-streamingdatabricks/databricks-agent-skillsComprehensive guide to Spark Structured Streaming for production workloads. Use when building streaming pipelines, working with Kafka ingestion, implementing Real-Time Mode (RTM), configuring triggers (processingTime, availableNow), handling stateful operations with watermarks, optimizing checkpoints, performing stream-stream or stream-static joins, writing to multiple sinks, or tuning streaming cost and performance.Data Engineering139spark-persona-support-agentreaddle/spark-cli-skillsYou are a support agent processing incoming requests through Spark's shared inboxes. Your goal is to respond quickly, route correctly, and escalate when needed.Data Engineering139spark-persona-team-leadreaddle/spark-cli-skillsYou are a team lead managing email workload distribution, shared inbox triage, and team coordination through Spark. Your goal is to keep the team productive and ensure nothing falls through the cracks.Data Engineering132databricks-ml-trainingdatabricks/databricks-agent-skillsTrain ML models on Databricks. Use for: classification/regression/deep-learning (XGBoost, scikit-learn, LightGBM, PyTorch) with Optuna, @prod/@challenger aliases, batch scoring (spark_udf for plain models, fe.score_batch for feature-store-backed), custom PyFunc, custom ResponsesAgent (LangGraph + UC Function/Vector Search); UC feature tables + FeatureLookup + point-in-time joins + Lakebase online store; declarative Feature Views (create_feature, DeltaTableSource, RollingWindow/SlidingWindow/TumblingWindow, materialize_features, streaming Kafka features). NOT for: endpoint ops (databricks-model-serving), MLflow evaluation (databricks-mlflow-evaluation).Data Engineering131netlifymembranedev/application-skillsNetlify is a platform for building, deploying, and scaling web applications. It's used by web developers and businesses to streamline their web development workflow with features like continuous deployment, serverless functions, and a global CDN.Data Engineering131spark-persona-sales-repreaddle/spark-cli-skillsYou are a sales rep / account manager tracking client relationships, deal progress, and follow-up cadence through Spark. Your goal is to keep every client conversation moving forward and ensure no deal goes cold.Data Engineering130spark-recipe-unsubscribe-auditreaddle/spark-cli-skillsAudit every newsletter pool, recommend unsubscribe candidates backed by engagement data, and execute only after the user approves the list. Spark supplies the data (senders, volumes, read flags, bodies); the agent owns classification, duplicate verification, and execution.Data Engineering126
ml-data-pipeline-architectureterrylica/cc-skillsPatterns for efficient ML data pipelines using Polars, Arrow, and ClickHouse. TRIGGERS - data pipeline, polars vs pandas, arrow formatData Engineering125labs64-netlicensingmembranedev/application-skillsLabs64 NetLicensing is a software licensing and license management platform. It's used by software vendors and developers to protect their applications and monetize them through various licensing models.Data Engineering124databricks-icebergdatabricks/databricks-agent-skillsApache Iceberg tables on Databricks — Managed Iceberg tables, External Iceberg Reads (fka Uniform), Compatibility Mode, Iceberg REST Catalog (IRC), Iceberg v3, Snowflake interop, PyIceberg, OSS Spark, external engine access and credential vending. Use when creating Iceberg tables, enabling External Iceberg Reads (uniform) on Delta tables (including Streaming Tables and Materialized Views via compatibility mode), configuring external engines to read Databricks tables via Unity Catalog IRC, integrating with Snowflake catalog to read Foreign Iceberg tablesData Engineering124pipelinermembranedev/application-skillsPipeliner is a CRM and sales automation platform designed to help sales teams manage leads, opportunities, and customer relationships. It's used by sales professionals and managers to streamline their sales processes, track performance, and close more deals.Data Engineering123
dbt-model-indexwarpdotdev/oz-skillsProvide a lookup index of dbt models (BigQuery tables) to guide query writing against a data warehouse. Use when you need to query, analyze, or look up data in a dbt-powered data warehouse, or when resolving a vague data question into the right BigQuery tables to query.Data Engineering123
azure-synapse-analyticsmicrosoftdocs/agent-skillsExpert knowledge for Azure Synapse Analytics development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Synapse SQL pools, serverless SQL, Spark pools, Synapse Link, or PolyBase/ELT data loading, and other Azure Synapse Analytics related development tasks. Not for Azure Data Factory (use azure-data-factory), Azure Data Explorer (use azure-data-explorer), Azure HDInsight (use azure-hdinsight), Azure Databricks (use azure-databricks).Data Engineering122
vfxdrawcall-ai/skillsAdd impact and feedback effects to a Three.js game with lightweight particle bursts — muzzle flashes, hit sparks, blood/dust, explosions, pickups — using pooled additive sprites or Points. Use when actions need visible punch (firing, impacts, deaths, explosions) or for ambient effects (smoke, embers, dust).Data Engineering120apache-supersetmembranedev/application-skillsApache Superset is a modern, open-source data exploration and visualization platform.Data Engineering117
syncfusion-wpf-sparklinesyncfusion/wpf-ui-components-skillsComprehensive guide for implementing Syncfusion WPF Sparkline (SfSparkline) controls in Windows Presentation Foundation applications. Use this when working with sparklines, mini charts, or trend visualization. This skill covers sparkline types (line, column, area, WinLoss), markers, track ball, range bands, axis controls, and segment customization for compact data visualization in WPF applications.Data Engineering112azure-hdinsightmicrosoftdocs/agent-skillsExpert knowledge for Azure HDInsight development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when working with HDInsight Spark/Hive/Kafka/HBase clusters, Ambari/Oozie pipelines, or Azure-integrated storage/BI, and other Azure HDInsight related development tasks. Not for Azure Databricks (use azure-databricks), Azure Synapse Analytics (use azure-synapse-analytics), Azure Stream Analytics (use azure-stream-analytics).Data Engineering110
smoke-test-ml-pipelineprobabl-ai/skillsThe minimal pytest that catches the "load → featurize → split" anti-pattern at iteration time, before it reaches production.Data Engineering102
migrating-dbt-project-across-platformsdbt-labs/dbt-agent-skillsUse when migrating a dbt project from one data platform or data warehouse to another (e.g., Snowflake to Databricks, Databricks to Snowflake) using dbt Fusion's real-time compilation to identify and fix SQL dialect differences.Data Engineering102
data-pipelinerightnow-ai/openfangData pipeline expert for ETL, Apache Spark, Airflow, dbt, and data qualityData Engineering99
social-sellinggtmagents/gtm-agentsUse when engaging prospects through LinkedIn, communities, and social channels to spark warm conversations and meetings.Data Engineering97
magic-etlstahura/domo-ai-vibe-rulesCreate, update, and execute Magic ETL dataflows programmatically via API and CLI. Covers DAG-based JSON dataflow definitions, input/transform/output node wiring, join operations, and execution lifecycle.Data Engineering95
pipelinejwilger/agent-skillsValue: Flow -- continuous, gated progression from slice to shipped code eliminates idle coordination overhead and makes quality evidence accumulate automatically.Data Engineering88
discover-datarand/cc-polymathAutomatically discover data pipeline and ETL skills when working with ETL, data pipelines, streaming, batch processing, data validation, or pipeline orchestration. Activates for data development tasks.Data Engineering85magic-etl-clistahura/domo-ai-vibe-rulesMagic ETL dataflows via community-domo-cli — list, get-definition, create, update, run, execution status; JSON DAG actions, transforms, joins. Use when automating dataflows with the community Domo CLI end-to-end. For REST/Java-CLI–first flows or mixed API patterns, use magic-etl instead.Data Engineering84
json-and-csv-data-transformationbesoeasy/open-skillsTransform data between JSON, CSV, and other formats with filtering, mapping, and flattening. Use when: (1) Converting API responses to CSV, (2) Processing data pipelines, (3) Extracting specific fields, or (4) Flattening nested structures.Data Engineering83
configuring-airflow-language-sdksastronomer/agentsConfigures Airflow to run language SDK tasks (Java, Go, and future native SDKs) — register a coordinator, map a queue to it, ensure the runtime/artifact on workers, and tune coordinator options. Use when the user wants Airflow to route a queue to a native-language coordinator, asks about the [sdk] coordinators/queue_to_coordinator settings, AIRFLOWSDKCOORDINATORS, jars_root, executables_root or other coordinator kwargs, task_startup_timeout, or why their native tasks aren't being picked up. Covers the shared routing mechanism plus per-coordinator options (e.g. JavaCoordinator, ExecutableCoordinator).Data Engineering83Other tasks
same rules, different job
