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Found 1,665 Skills
Guide for using Nushell for structured data pipelines and scripting. Use when writing shell scripts, processing structured data, or working with cross-platform automation.
CI/CD pipeline design with GitHub Actions, Docker, Kubernetes, Helm, and GitOps patterns
Deterministic CI/CD interaction patterns. Push-and-wait discipline, failure triage, self-healing for lint/format/infra failures, structured output for pipeline consumption. Activate when interacting with CI/CD systems.
Master Node.js streams for memory-efficient processing of large datasets, real-time data handling, and building data pipelines
Build production-ready systems with stability patterns: circuit breakers, bulkheads, timeouts, and retry logic. Use when the user mentions "production outage", "circuit breaker", "timeout strategy", "deployment pipeline", or "chaos engineering". Covers capacity planning, health checks, and anti-fragility patterns. For data systems, see ddia-systems. For system architecture, see system-design.
Manages Python project dependencies with uv. Learn how to add, remove, and updates dependencies, organize them into groups (dev, test, lint, docs), pin versions, handle conflicts, and manages lock files for reproducible installations across environments. Use when adding or updating packages, organizing development dependencies, resolving version conflicts, or managing lock files in CI/CD pipelines.
Full pipeline audio system generator. Use when building complete game audio systems that span MetaSounds + Blueprint + Wwise layers, generating AAA project structures, or orchestrating multi-layer audio from a natural language description.
Guides Docker, CI/CD pipelines, deployment strategies, infrastructure as code, and observability setup. Use when writing Dockerfiles, configuring GitHub Actions, planning deployments, setting up monitoring, or when asked about containers, pipelines, Terraform, or production infrastructure.
Generate text embeddings and rerank documents via Together AI. Embedding models include BGE, GTE, E5, UAE families. Reranking via MixedBread reranker. Use when users need text embeddings, vector search, semantic similarity, document reranking, RAG pipeline components, or retrieval-augmented generation.
MongoDB and PostgreSQL database administration. Databases: MongoDB (document store, aggregation, Atlas), PostgreSQL (relational, SQL, psql). Capabilities: schema design, query optimization, indexing, migrations, replication, sharding, backup/restore, user management, performance analysis. Actions: design, query, optimize, migrate, backup, restore, index, shard databases. Keywords: MongoDB, PostgreSQL, SQL, NoSQL, BSON, aggregation pipeline, Atlas, psql, pgAdmin, schema design, index, query optimization, EXPLAIN, replication, sharding, backup, restore, migration, ORM, Prisma, Mongoose, connection pooling, transactions, ACID. Use when: designing database schemas, writing complex queries, optimizing query performance, creating indexes, performing migrations, setting up replication, implementing backup strategies, managing database permissions, troubleshooting slow queries.
Before running Python scripts or installing packages, check for existing virtual environments and reuse them if found. If no virtual environment exists, ask the user to choose: (1) Create new venv in current directory (recommended), (2) Use system Python directly, or (3) Create venv at custom path. This applies to: running .py files, using pip/uv pip install, or any task requiring third-party packages. Exceptions: simple one-liners using only Python standard library.
Transform creative ideas into professional, production-ready screenplays optimized for AI video generation pipelines. Converts raw concepts into structured scene-by-scene narratives with rich visual descriptions, proper screenplay formatting, and XML-tagged output for seamless integration with image/video generation tools (imagine, arch-v). USE WHEN: Converting story ideas into screenplay format, preparing content for AI video pipelines, structuring narratives for 5-10 minute short films, generating visual-rich scene descriptions for image generation. WORKFLOW: Raw idea → Scene breakdown → Visual enhancement → Professional formatting → XML-tagged markdown output OUTPUT: Markdown document with XML-wrapped scenes, rich visual descriptions, proper screenplay elements (sluglines, action, dialogue), and metadata for pipeline processing.