reverse-etl-and-operational-data-serving
Guides agents through reverse ETL and operational data serving workflows. Use when sending curated warehouse data to business systems, SaaS tools, APIs,…
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Updated 11-01 00:15
17,214 results
Guides agents through reverse ETL and operational data serving workflows. Use when sending curated warehouse data to business systems, SaaS tools, APIs,…
Guides agents through batch and distributed data processing design. Use when implementing or reviewing Spark-based pipelines, or managed distributed runtimes…
Guides agents through Unity Catalog governance workflows for Databricks lakehouses. Use when defining catalogs, schemas, external locations, access boundaries,…
Provides a compatibility alias for the main data engineering entry skill. Use when an existing setup still points at the legacy start-here file.
Standard operating procedure for research experiments, data analysis, and visualization. Covers Python/R script execution, statistical analysis, data wrangling…
SQL and NoSQL schema design with normalization, indexing, and migration patterns. Use when designing database schemas, creating tables, optimizing slow…
Text embeddings for semantic search and similarity. Use when converting text to vectors, choosing embedding models, implementing chunking strategies, or…
Use for Fermi estimation, or when a rough number is needed fast: "roughly how many...", "ballpark the cost", "estimate capacity or market size", "is this even…
Agent-callable Google Analytics 4 (GA4) tools — run analytics reports, discover the dimensions and metrics a property supports, navigate accounts and…
A tool for browsing Sister Zheng's stock analysis diary. Supports viewing the latest n diary entries, counting the total, querying by date, querying by stock name/code, and full-text keyword search.
Build data ingestion pipelines for batch and streaming data from multiple sources. Covers extraction strategies, format normalization, deduplication,…
Use Redis effectively for caching, pub/sub messaging, rate limiting, distributed locks, and session storage. Covers data structure selection, expiration…
Comprehensive skill for Microsoft GraphRAG - modular graph-based RAG system for reasoning over private datasets
Query and analyze OCI order detail data from StarRocks via DuckDB. Always exports to CSV before analysis. Supports basic, aggregation, customer, sales,…
Web full-stack attacks: SQLi/command injection/SSTI/XSS/SSRF/NoSQL, authentication JWT/OAuth/SAML, LFI/upload, Tomcat/WS/STOMP/XFF/PATH_INFO/CDN502/Wangsu JS challenge bypass. Use when testing Web injection, auth bypass,…
Comprehensive guide to quantitative trading development with WonderTrader/wtpy, integrating official documentation, community notes, and practical cases. Covers the full workflow of strategy development, backtesting, simulation, live trading, data management, and monitoring/operations for the wtpy Python framework and the WonderTrader C++ core.
SQL syntax conversion skill across big data engines (DML/DDL/stored procedures). Covers rewrite scenarios such as identifiers, data types, functions, query syntax, distribution/partitioning strategies, stored procedures/functions, external tables, etc. Synapse → Hologres is currently implemented, and the framework is for other engine pairs (such as SQL Server → MaxCompute, Hive →…
Use when preparing a medical-imaging dataset (DICOM/NIfTI) for modelling. Profiles spacing, orientation, intensity, label integrity, foreground fraction and…
Audits database server hardening for PostgreSQL, MySQL/MariaDB, Redis, and MongoDB — network placement and binding, transport encryption, authentication…
SQL analysis skill for Ascend PyTorch Profiler / msprof DB (such as ascend_pytorch_profiler*.db, msprof_*.db). Converts natural language questions (operator duration, communication, dispatch, scheduling, schema/table queries) into safe, executable SQL, and extracts table structure details from official documentation as needed.
Expert skill dedicated to diagnosing "fast/slow cards" from Ascend cluster Profiling performance data. When the user provides a [cluster performance data directory/path] and requests analysis of [fast/slow cards], [slow nodes], [load imbalance], or [cluster bottlenecks], this skill must be triggered. This skill automatically receives the cluster path and dispatches relevant tools to output the macroscopic qualitative assessment and microscopic root causes of fast/slow cards (such as Host dispatch bottlenecks or operator computation degradation).
When the user provides performance data collected by the MindStudio profiler (framework profiler, msprof command line), validate data completeness, collection status, and key configurations to ensure that subsequent analysis tools can run properly.
Use this skill whenever you are about to create ANY chart, graph, plot, dashboard, or data visualization, in ANY output medium — an HTML or React artifact,…
Detect anomalies in Axiom datasets using statistical analysis. Use when looking for unusual patterns, volume spikes, outliers, or new error types in…