Inventory available datasets, instrumentation gaps, and data quality considerations for the initiative. — from general/general-misc
Data Augmentation Pipeline - Auto-activating skill for ML Training. Triggers on: data augmentation pipeline, data augmentation pipeline Part of the ML Training skill category.
Automated data quality and transformation capabilities for Dataform/dbt/BigQuery
Check data availability in SAP Datasphere tables by querying configured sources with dimension-based grouping.
L1 supplement - audits storage / data-availability chains (Arweave / Celestia-class) for unenforced data commitments: producer commits to data inclusion but the validator never…
Backup and manage game data including maps, NPCs, and configurations. Use when the user wants to backup data, create snapshots, export data, or restore from backups.
Richtet einen sicheren virtuellen Data Room für externe Counsel, Behörden und US-Discovery ein – Zugang, Privilegierung, Protokollierung im Internal Investigations Praxis.
Gestione data breach GDPR con valutazione rischio, notifica al Garante entro 72h e stima sanzioni. Usa quando l'utente segnala una violazione di dati personali, chiede come…
Data breach incident response with ENISA severity scoring, notification timelines, and compliance tracking. Use for breach assessment and response. — from general/general-misc
Data breach incident response with ENISA severity scoring, notification timelines, and compliance tracking. Use for breach assessment and response.
Get your personal info off people-search and data-broker sites — a prioritized opt-out plan that targets the sites that matter and keeps them from reappearing.
Build an interactive HTML dashboard with charts, filters, and tables
Guides agents through data catalog, discovery, and metadata quality workflows. Use when publishing datasets, improving discoverability, curating lineage metadata, or making data…
Data Catalog Updater - Auto-activating skill for Data Pipelines. Triggers on: data catalog updater, data catalog updater Part of the Data Pipelines skill category.
Search and visualize the world's data - get charts, insights, and embeddable knowledge cards for finance, economics, demographics, sports, and more — from…
Data classification framework including sensitivity levels, handling requirements, labeling, and data lifecycle management
Use when preparing raw data for modeling — handling missing values, duplicates, inconsistent types, outliers, and bad categorical values.
Complete workflow for time series datasets (Energy, Manufacturing, Climate) on Kaggle to Data Annotation platform (data.smlcrm.com).
Writes clear, step-by-step instructions for cleaning a messy or inconsistent dataset — specifying exactly what needs to be standardised, corrected, or removed to make the data…
Clean a messy dataset methodically — the profiling pass that finds what's actually wrong (dupes, format drift, phantom spaces, mixed types), the fix order that doesn't corrupt…
Build robust processes for data cleaning, missing value imputation, outlier handling, and data transformation for data preprocessing, data quality, and data pipeline automation
Clean and standardize vehicle insurance CSV/Excel data. Use when handling missing values, fixing data formats, removing duplicates, or standardizing fields.
Guides creation, design, and maintenance of Calculated Insights in Data Cloud: SQL authoring, dimension/measure definition, scheduling, streaming insights, and insight…
Use when designing or managing Data Model Objects (DMOs) in Salesforce Data Cloud — covers DMO schema design, subject area governance, data relationships between DMOs, XMD…
Step-by-step guidance for configuring Data Cloud data streams: connecting source connectors, mapping Data Lake Objects (DLOs) to Data Model Objects (DMOs), enabling identity…
Use when grounding an Agentforce agent with Data Cloud retrievers, DMO selection, chunking, and freshness windows.
Use when enabling Data Cloud (Data 360) in an org, creating data spaces, assigning permission sets, registering ingestion API sources, or configuring activation targets.
Use when building integrations or replacing synthetic demos with real data sources. Requires source contracts, idempotent ingestion, validation, observability, and fixture-backed…
Create or repair a durable data context containing schema, grain, metric definitions, lineage, ownership, freshness, and quality caveats.
Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts.
Create, validate, test, and manage data contracts using the Open Data Contract Specification (ODCS) and the datacontract CLI.
Data contracts สำหรับกำหนด schema, quality expectations และ SLAs ระหว่าง data producers และ consumers
Convert between CSV, TSV, Excel, JSONL, Parquet, and other tabular formats
Convert data between formats (JSON, XML, CSV, YAML, TOML). Use when transforming data structures or migrating between data formats.
Warehouse cost reduction, auto-scaling, query optimization, and lifecycle policies for data infrastructure.
대법원 법원경매정보(courtauction.go.kr) 부동산 매각공고를 매각기일·법원·기일/기간 입찰 기준으로 조회하고, 각 공고를 사건번호·용도·주소·감정평가액·최저매각가로 펼쳐서 보여줍니다. 법원사무소 코드와 사건번호로 단건 직접 조회도 지원합니다.
Verifica datos del plan de negocio contra fuentes externas. Delega a investigación web para confirmar o refutar datos numéricos y hechos concretos.
Prüft personenbezogene Daten, Cybervorfälle, KI-Systeme, SaaS-Verträge, Open Source und IT-Abhängigkeiten im Private Equity Praxis.
Master data data cleansing automation with comprehensive coverage of concepts, implementation, optimization, and production best practices.
Gouvernance des données incluant catalogues, lineage, qualité, ownership, politiques et metadata management.
Transformation de données avec dbt — models, tests, sources, macros et documentation automatisée. Se déclenche avec "dbt", "data build tool", "dbt model", "dbt test", "tr — from…
Web and App implementation guide for Data-Dense Design. Trigger when user wants professional tools, maximum information density, and expert interfaces (like Bloomberg terminals or…
Für Data: Dokumentenmatrix, Lückenliste und Nachforderung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.
Modélisation dimensionnelle pour le data warehousing — schéma en étoile, flocon, tables de faits et dimensions, slowly changing dimensions.
Complex data deserves multiple view modes — grid, list, table — chosen by the user based on their task.
Shared rules for any data engineering work — warehouse is read-only via Managed-MCP/OAuth, sample-then-scale on every query, every reported metric traces to a logged query and…
GIS integration, sensor data, occupancy analytics, space syntax analysis, urban data analytics, climate data processing, and API data sources for evidence-based AEC computational…
Create dashboard panel components with integrated resilient data services, combining UI construction and data fetching into a unified pattern.
Comprehensive audit of data system effectiveness — lifecycle scoring across Capture, Storage, Recall, and Action dimensions for all data systems in the project.
데이터 엔지니어링·클라우드 글의 기술 깊이를 만든다. GCP(BigQuery/Dataflow/Pub-Sub/Composer)와 OSS 데이터 스택(Spark/Airflow/Kafka/Flink/dbt/Iceberg)의 아키텍처·실행 가능한 코드·트레이드오프·실제 스키마를 02_sme_notes.md에 작성한다.
Use when a task needs the judgment of a Data Entry Keyer — resolving an illegible or ambiguous source-document field before keying it, running key-verification (double-key)…
Design ETL / ELT pipelines — extraction, transformation, load — with reproducible steps, schema evolution, quality checks, and observability.
Analyze data evolution patterns in construction organizations. Assess digital maturity and data strategy for construction companies
Обмен данными 1С. Используй когда нужно реализовать или диагностировать планы обмена, РИБ, регистрацию изменений, загрузку/выгрузку сообщений, конфликт данных или контракт обмена.
Profile and explore datasets to understand their shape, quality, and patterns before analysis. Use when encountering a new dataset, assessing data quality, discovering column…
Systematic database and table profiling for DBX Studio. Use when a user wants to understand their data, explore schema structure, or profile a dataset.
Profile and explore a dataset to understand its shape, quality, and patterns
Fast read-only exploration agent for querying structured data files using dasel v3 — discovers structure, lists keys, samples arrays, extracts values across JSON, YAML, TOML, XML,…
Export analysis results, data tables, and formatted spreadsheets to Excel files using openpyxl. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).
Use when exporting data for ad platforms (Google Ads, Meta) or working with project datasets. Documents exact CSV formats for Enhanced Conversions, Customer Match, and project…