DevOps & Cloud Skills

Help with abapGit workflows including repository setup, cloning, serialization, branching strategies, transport-vs-git workflows, CI/CD integration, and .abapgit.xml configuration. Use when users ask about abapGit, git for ABAP, ABAP version control, abapGit clone, abapGit pull, abapGit push, branching strategy for ABAP, abapGit configuration, serialization, deserialization, transport vs git, gCTS, abapGit CI/CD, or managing ABAP code in git repositories. Triggers include "set up abapGit", "clone a repo", "push ABAP to git", "abapGit branching", "abapGit configuration", ".abapgit.xml", "transport vs git", or "CI/CD for ABAP".

Create cinematic HTML presentations with AI video backgrounds, deployed to GitHub Pages. Use for: slides, presentation, deck, cinematic slides, video presentation, animated slides, live presentation.

Deploy static or interactive frontend content to GitHub Pages using gh CLI. Use when the user wants to publish, share, or make accessible any HTML/CSS/JS content - including demos, prototypes, visualizations, landing pages, portfolios, documentation, interactive tools, games, or any browser-based project. Activate whenever content needs to be publicly viewable via URL, not just when "website" is explicitly mentioned.

AI risk assessment using NIST AI RMF 1.0 framework. Evaluate AI systems across 4 core functions (Govern, Map, Measure, Manage) for trustworthy and responsible AI deployment.

> ☁️ DevOps & Cloud Infrastructure skill suite derived from alirezarezvani/claude-skills. CI/CD pipelines, container orchestration, IaC, monitoring and incident response. Provides 10 specialised commands for devops, cloud, docker workflows.

Build interactive, click-through architecture diagrams for software systems — a self-contained single HTML file with animated step-by-step flows, mode toggles (dev/prod, offline/online, v1/v2), dark/light theme, and a side panel with payload details, plus a companion markdown description. Use when the user wants to visualize or design a system: architecture diagram, service map, data flow, RAG/agentic flow, microservices topology, integration diagram, CI/CD or data/ETL pipeline, multi-agent system, or onboarding diagram — or to design a new service's flows before building. Natural-language triggers: 'I'm building X, what should the flow look like', 'pokaż jak działa system', 'diagram architektury', 'wizualizacja systemu', 'klikany diagram'. Do NOT use for static diagrams that belong inline (Mermaid/PlantUML), slide decks, or printable/PDF handouts — this produces interactive HTML for browser consumption.

> ☁️ DevOps & Cloud Infrastructure skill suite derived from BehiSecc/awesome-claude-skills. CI/CD pipelines, container orchestration, IaC, monitoring and incident response. Provides 10 specialised commands for devops, cloud, docker workflows.

Expert AWS solution architecture for startups focusing on serverless, scalable, and cost-effective cloud infrastructure with modern DevOps practices and infrastructure-as-code

Health checks, metrics, alerting ve rollback stratejileri.

CI/CD pipeline, GitHub Actions, automated deployment, release management, production shipping, and software delivery.

Docker image optimization patterns including multi-stage builds, layer caching, security hardening, and size reduction techniques. Use when building Docker images, optimizing container size, improving build performance, or implementing Docker security best practices. Reduces image sizes by 70-90% and build times by 50-80%.

Expert Kubernetes specialist for production-grade container orchestration. Invoke for cluster management, workload deployment, security hardening, and performance optimization. Keywords: Kubernetes, K8s, kubectl, Helm, RBAC, NetworkPolicy.

Distributed systems architect specializing in microservices design patterns. Invoke for service boundaries, domain-driven design, saga patterns, event sourcing, service mesh, distributed tracing. Keywords: microservices, service mesh, distributed systems, Kubernetes, event-driven.

Design and implement Internal Developer Platforms (IDPs) with self-service capabilities, golden paths, and developer experience optimization. Covers platform strategy, IDP architecture (Backstage, Port), infrastructure orchestration (Crossplane), GitOps (Argo CD), and adoption patterns. Use when building developer platforms, improving DevEx, or establishing platform teams.

Senior Terraform engineer for infrastructure as code, multi-cloud provisioning, and modular architecture. Invoke for Terraform modules, state management, provider configuration, and enterprise IaC patterns.

Create HTML system architecture diagrams — microservice maps, dependency graphs, deployment topologies, data ownership maps, integration diagrams. Useful during incidents, design reviews, onboarding, and capacity planning. Use whenever the user wants to visualize, document, or explain how a system fits together — across services, regions, queues, caches, databases, or organizational boundaries. Reach for this whenever the explanation would otherwise involve sentences like "service A talks to service B which writes to queue C".

Reviews opportunities in the sales pipeline to identify stuck deals, missing next steps, weak qualification, and unbalanced stages. Use when user asks "how is my pipeline looking", "analyze pipeline health", "which deals are stuck", "pipeline review", "find at-risk deals", "identify stalled opportunities", or "audit my open deals".

Prepares production launches. Use when preparing to deploy to production. Use when you need a pre-launch checklist, when setting up monitoring, when planning a staged rollout, or when you need a rollback strategy.

Read the Convex deployment's 72h insights (read limits, OCC contention), root-cause each event in code, report evidence-backed perf/cost findings with fixes.

Classify + announce the target Convex deployment before any deployment-affecting command; fresh explicit consent for prod actions; session read-only mode.

Set and wire Convex deployment env vars / secrets for the app.

Query a running Convex app's logs + health in natural language (official MCP): failures, slow/expensive functions, deploy causality — scoped, evidence-backed, with a dashboard deep link.

Migrate schema + backfill data on a deployed Convex app using @convex-dev/migrations.

Audit and optimize an existing Convex app: security, scale, upgrades, observability.

Rehearse a live-app schema change + backfill on a snapshot-seeded preview deployment, verify, then promote the proven change to prod with the snapshot as rollback.

Set up Sentinel production error capture in your own Convex deployment.

>- Facilitates a zero-based AI-first process redesign session that helps a team reimagine an existing work process as AI-first. Guides them through framing, idea expansion, current-state task map, a future-state swimlane blueprint tagging each step AI-owned / Hybrid / Human-led, an AI-Agents-&-Skills summary table, and a next-sprint capability backlog. Weighs the full range of AI building blocks — process change, knowledge, tools, reusable skills, agents, connected agents — instead of defaulting to an agent. Use when the user wants to redesign a process for AI, make a workflow AI-first, map which tasks AI should own, or find AI or agent opportunities in a process. It shows WHERE AI could help; it does NOT build or deploy the agents or skills themselves. Do NOT use to build a specific agent or skill, for a one-off automation with no process to rethink, or for employee performance evaluation.

Use this skill when a Power Automate flow triggers the agent with a payload describing an unknown source column from a lab results file that broke an Azure Data Factory ingestion pipeline. The skill semantically matches the source column against the canonical clinical schema indexed in Azure AI Search, scoped first by the sending lab and then by clinical domain, and writes a suggested destination-column mapping to the Dataverse review queue for a clinical informatics steward to approve. Also activates on manual invocations like "map this lab column", "the ADF pipeline failed on column X, what should it map to", or "suggest a canonical column for this lab feed field".

Use when the user asks to set up, run, or check a scheduled regulation, law, or regulatory-guidance monitor or tracker — triggers include "set up a regulation tracker for X", "monitor [regulation] for me", "run my regulation monitor", "what changed on [regulation] this week", or an unattended scheduler invoking a saved profile. On first invocation walk interactive setup (topics, jurisdictions, cadence, delivery), auto-discover the top authoritative sources per topic, and STOP for user confirmation before any monitoring. On subsequent runs visit only the locked source list plus user seeds, classify items, flag team-relevant ones via a WorkIQ-derived keyword match, and render a self-contained HTML dashboard with client-side sortable columns. Do NOT use for one-off legal research, reading a single document, computing compliance liability or filing position, or non-regulatory news monitoring.

RouterOS /container subsystem for running OCI containers on MikroTik devices. Use when: enabling containers on RouterOS, setting up VETH/bridge networking for containers, managing container lifecycle via CLI or REST API, building OCI images for RouterOS, configuring container environment variables, troubleshooting container issues, or when the user mentions RouterOS container, /container, VETH, device-mode container, or MikroTik Docker.

RouterOS /app YAML format for container applications (7.21+ builtin app, 7.22+ custom YAML creation). Use when: writing or validating RouterOS /app YAML files, working with MikroTik container apps, building docker-compose-like definitions for RouterOS, creating /app store schemas, debugging /app validation errors, or when the user mentions /app, tikapp, or RouterOS container YAML.

Create and review .gitlab-ci.yml files based on GitLab CI best practices and company standards. Use when creating CI/CD pipelines for new projects, reviewing existing .gitlab-ci.yml, or optimizing pipeline configuration.

Query and manage Grafana dashboards, alert rules, and data sources via HTTP API. Use when viewing dashboards, troubleshooting alerts, checking service metrics, finding data sources, or when Grafana, monitoring, alerts, dashboards, or observability is mentioned.

Query Prometheus monitoring metrics and alert rules. Use when the user needs to check CPU/memory/disk utilization, service health, audit alert rules, analyze capacity trends, or mentions Prometheus, PromQL, metrics monitoring, or targets.

Manage Kubernetes cluster resources via kubectl. Use when user needs to view, troubleshoot, or modify K8s workloads across multiple clusters.

Create and configure Sentry projects across staging/production environments via REST API. Use when user needs to onboard a new service to Sentry, create Sentry projects, or set up error monitoring for a new application.

Audit Terraform codebases for security, cost, code quality, and architecture issues. Use when reviewing Terraform projects, checking infrastructure-as-code compliance, or assessing AWS resource configurations for best practices.

Query Sentry errors, triage issues, and check release health via REST API. Use when debugging exceptions, investigating crash reports, triaging error issues, checking release stability, or any error monitoring and issue tracking task. Also triggers on mentions of Sentry, errors, exceptions, crashes, stack traces, or error rates.

Handles LLM-as-judge and code evaluator workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and continuous monitoring. Use when the user mentions create evaluator, LLM judge, code evaluator, hallucination, faithfulness, correctness, relevance, run eval, score spans, score experiment, trigger-run, column mapping, continuous monitoring, or improve evaluator prompt.

Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features. Supports any LLM provider (e.g. OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM). Use when the user mentions AI integration, LLM provider credentials, create integration, list integrations, update credentials, delete integration, or connecting an LLM provider to Arize.

Adds Arize AX tracing to an LLM application for the first time. Detects the stack, routes to the single matching integration doc, wires auto-instrumentation after user confirmation, and verifies traces land. Use when the user wants to instrument their app, add tracing from scratch, set up LLM observability, integrate OpenTelemetry or openinference, or get started with Arize tracing.

Audit the infra and DevOps domain - CI/CD, deployment, IaC, secrets management, environments, logging, observability. Run as part of /audit Phase E.

Audit the cost and billing risk domain - runaway loops, unbounded LLM/API calls, missing rate limits on paid services, infrastructure cost amplifiers. Run as part of /audit Phase E.

Use after deployments to verify health endpoints, run API smoke tests, and confirm release integrity with CLI checks.

Audit the current project for stale or broken orchestration setup. Verifies monitoring.md, AGENTS.md/CLAUDE.md, graphify freshness, dead script references, placeholder values still in YAML frontmatter. Read-only - never mutates. Use after /monitoring-setup, after pulling someone else's setup, or when something feels off.

Generate a Confluent Cloud topic creation script with idempotency checks. Use when the user asks to create a topic, provision topics, or write a `create-topics.sh` for Confluent Cloud. Do NOT trigger for self-managed Apache Kafka, schema registration, Terraform generation, or Kafka Streams topology authoring.

Create Confluent-specific skills for external users. Use this skill when users want to create, build, or author a new skill related to Confluent Cloud, Confluent Platform, Apache Kafka, WarpStream, Flink, Connectors, Schema Registry, Tableflow, CDC pipelines, or any Confluent product. Skills can be use-case focused (like data enrichment, CDC to Tableflow, stream processing workflows) or component-specific (like a Flink skill, Schema Registry skill, or Connector skill). Do NOT use this skill when users want to directly use Confluent products (e.g., build a pipeline, write a producer, deploy Flink SQL) — use the appropriate product-specific skill instead. This skill is specifically for creating new skills, not for using existing ones.

Use when the user wants to integrate a Kafka client into an existing application or scaffold a Java Kafka client project (Maven or Gradle based) for Confluent Cloud, local Docker, or WarpStream. Covers the Apache Kafka Java clients (KafkaProducer/KafkaConsumer/KafkaShareConsumer) with Avro, JSON Schema, or Protobuf serializers. Also use when the user wants to optimize Java Kafka client configuration for WarpStream. Do NOT trigger for Kafka Streams apps (use kafka-streams-programming), Flink, connectors, or Kafka Python client (use developing-kafka-python-client).