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Analyzes legacy COBOL programs and JCL jobs to assist with migration to modern Java applications. Extracts business logic, identifies dependencies, generates migration reports, and creates Java implementation s...
Analyzes and assists with Fujitsu mainframe systems including FACOM, PRIMERGY, BS2000/OSD, OSIV/MSP, OSIV/XSP, NetCOBOL, PowerCOBOL, and Fujitsu JCL. Extracts business logic from Fujitsu COBOL programs, analyze...
Guides database migration projects including engine changes (MySQL to PostgreSQL, Oracle to PostgreSQL, SQL Server to PostgreSQL), version upgrades, cloud migrations (on-premise to RDS/Cloud SQL/Azure Database)...
Design, standardize, and implement ECharts-based visualizations and themes for InsightPulseAI dashboards, Superset plugins, and OpEx UI (AntD + M3 + ECharts).
Database migration management with Alembic for SQLAlchemy. Use when creating or modifying database schemas, tables, or indexes.
Database operations for BAZINGA orchestration system. This skill should be used when agents need to save or retrieve orchestration state, logs, task groups, token usage, or skill outputs. Replaces file-based st...
Discover, use, or subclass existing Dagster integration components (dbt, Looker, PowerBI, Fivetran, etc.). Handles configuration-file-based components (dbt, Sling) and API-based components (Fivetran, PowerBI) a...
Dagster+ Cloud Onboarding Skill This skill automates the setup of Dagster+ Cloud projects, including
Use for Supabase schema, RLS policies, API design, and AI integration settings.
Execute SQL queries and data modifications on PostgreSQL databases running in Docker containers. Auto-detects running PostgreSQL containers and executes SELECT, INSERT, UPDATE, and DELETE operations. Use when w...
System design, technical strategy, architecture decisions, tradeoff analysis, and complex debugging for BOMvault's dual-cluster PostgreSQL, NATS pipeline, and multi-tenant microservices.
Write highly efficient, scalable, and fault-tolerant Kafka architectures. Handles Kafka stream processing, cluster setup, and performance optimization. Use PROACTIVELY for Kafka architecture design, troubleshoo...
Expert in Celery for distributed task queue management, optimizing task execution, and ensuring robust Celery deployments.
Backend patterns for Convex serverless database including schema definitions, queries, mutations, indexes, and Clerk authentication integration. Use for database operations, API endpoints, auth checks.
Handles customer data responsibly by answering questions ABOUT data without ever seeing the data directly. Use when querying Redis, databases, logs, or any source containing customer information like JIDs, emai...
Expert database design, queries, and optimization for both SQL (Neon serverless PostgreSQL) and NoSQL (MongoDB) databases. Use when designing database schemas, writing queries, creating migrations, optimizing p...
Instructions for generating synthetic airline data with Synth CLI and loading it into SQLite.
Apache Kafka event publishing with circuit breaker, failure recovery, and Smartico CRM integration. Use when: publishing domain events, consuming messages, handling event failures, or integrating with Smartico.
High-performance DataFrame library usage. Covers Lazy API, Wrangling, Aggregation.
This skill provides Drizzle ORM patterns and database conventions for the fitness app. Use when creating queries, implementing RLS policies, or working with database schemas.
Creates JPA entities following best practices.
Execute data-driven refactorings from data-driven-refactor reports. Use this when the user wants to implement data extraction recommendations by creating data files and refactoring scripts.
Convert natural language queries to SQL for PostgreSQL databases. Use this skill when users want to query pg_mcp_test_small (blog), pg_mcp_test_medium (ecommerce), or pg_mcp_test_large (ERP) databases using nat...
Transform, clean, and reshape data using pandas and numpy for ETL and data preprocessing. WHEN: Manipulating DataFrames, cleaning datasets, reshaping data (pivot, melt), merging/joining tables, data normalizati...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.