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Found 550 Skills
Authoritative reference for the neo4j-agent-memory Python package — a graph-native memory system for AI agents built on Neo4j — and for the hosted service (NAMS) at memory.neo4jlabs.com. Use this skill whenever the user mentions neo4j-agent-memory, agent memory with Neo4j, context graphs, the POLE+O model, MemoryClient/MemorySettings, the memory MCP server, or any of the framework integrations (LangChain, PydanticAI, CrewAI, AWS Strands, Google ADK, Microsoft Agent Framework, OpenAI Agents, LlamaIndex). Also use when the user mentions the hosted service at memory.neo4jlabs.com, NAMS, the Neo4j Agent Memory Service, the `nams_` API key prefix, or the hosted MCP endpoint. Also use when writing documentation, blog posts, tutorials, PRDs, or code samples for the project, when comparing agent memory approaches, or when positioning graph-native memory against vector-only approaches — even if the user doesn't explicitly name the package.
Update Margin Dashboard with Fidelity balance data and calculate margin-living strategy metrics. Monitors margin balance, interest costs, coverage ratios, and scaling thresholds. Triggers safety alerts for large draws and provides time-based scaling recommendations. Use when updating margin, balances, coverage ratio, or margin strategy analysis.
Full GSAP v3 mastery for interactive websites: core tweens/timelines, eases, staggers, keyframes, modifiers, utilities, plus complete plugin coverage (ScrollTrigger, ScrollTo, ScrollSmoother, Flip, Draggable, Inertia, Observer, MotionPath, DrawSVG, MorphSVG, SplitText, ScrambleText, TextPlugin, Physics2D/PhysicsProps, CustomEase/Wiggle/Bounce, GSDevTools). Includes Next.js/React patterns (useGSAP, gsap.context cleanup), responsive matchMedia, reduced-motion accessibility, performance best practices, and debugging playbooks.
This skill should be used when creating or configuring CI/CD pipeline files for automated testing, building, and deployment. Use this for generating GitHub Actions workflows, GitLab CI configs, CircleCI configs, or other CI/CD platform configurations. Ideal for setting up automated pipelines for Node.js/Next.js applications, including linting, testing, building, and deploying to platforms like Vercel, Netlify, or AWS.
General-purpose diagramming tool using drawio XML format with 8900+ stencils. Best for custom diagrams requiring pixel-perfect positioning, diagrams with vendor-specific icons (AWS, Azure, Cisco), or any diagram not covered by specialized skills. Use network skill for network topology, uml skill for UML diagrams, architecture skill for layered system views. NOT for simple flowcharts (use mermaid) or data-driven charts (use vega).
This skill should be used when users need to sync/promote configuration from staging (aws-staging) to production (aws-prod) environment. It handles image tag synchronization, identifies configuration differences, and manages the promotion workflow. Triggers on requests mentioning "sync to prod", "promote to production", "update prod images", or comparing staging vs production.
Use when deploying a Bknd application to production hosting. Covers Cloudflare Workers/Pages, Node.js/Bun servers, Docker, Vercel, AWS Lambda, and other platforms.
Run ScoutSuite for multi-cloud security auditing. Collects configuration data from AWS, Azure, GCP, Oracle, and Alibaba Cloud and generates an interactive security report.
Guides development with SAP AI Core and SAP AI Launchpad for enterprise AI/ML workloads on SAP BTP. Use when: deploying generative AI models (GPT, Claude, Gemini, Llama), building orchestration workflows with templating/filtering/grounding, implementing RAG with vector databases, managing ML training pipelines with Argo Workflows, configuring content filtering and data masking for PII protection, using the Generative AI Hub for prompt experimentation, or integrating AI capabilities into SAP applications. Covers service plans (Free/Standard/Extended), model providers (Azure OpenAI, AWS Bedrock, GCP Vertex AI, Mistral, IBM), orchestration modules, embeddings, tool calling, and structured outputs.
Cloud infrastructure design and deployment patterns for AWS, Azure, and GCP. Use when designing cloud architectures, implementing IaC with Terraform, optimizing costs, or setting up multi-region deployments.
Audit rapidly generated or AI-produced code for structural flaws, fragility, and production risks.
RabbitMQ message broker with AMQP protocol. Covers exchanges, queues, bindings, and messaging patterns. Use for reliable message delivery and complex routing scenarios. USE WHEN: user mentions "rabbitmq", "amqp", "exchanges", "routing patterns", "topic exchange", "fanout", asks about "message routing", "work queues", "request/reply", "flexible routing" DO NOT USE FOR: high-throughput streaming - use `kafka` or `pulsar`; cloud-native - use `nats`; AWS-native - use `sqs`; JMS required - use `activemq`; simple pub/sub - use `redis-pubsub`