DevOps Claude Skills
4 344 DevOps skills from 392 authors. They ship releases, run infrastructure and keep watch over what is deployed. Half of them fit into 2 094 tokens or less — that is what one costs your context window when the agent loads it. 513 ship runnable scripts rather than instructions alone. 28 of them cannot work without an MCP server, most often rube. We also found 649 copies of these same skills sitting in other people's repositories — counted once here, not 649 times.
4 344 unique 392 authors 4 updated this month 579 from vendors
Review Kafka Connect connector configurations for common misconfigurations using the Lenses MCP server. Checks error handling, DLQ setup, converters, transforms, task count and task health. Use when user says "review connectors", "check connector configs", "why is my connector failing" or asks about Kafka Connect configuration. Do NOT use for creating, deploying or controlling connectors.
Generate a TestContainers Java test class that spins up ShadowTraffic in-process to populate a Kafka topic with synthetic data during tests. Invokes the kafka-shadowtraffic skill to build the ShadowTraffic config, then adapts it for a containerized test network and scaffolds a JUnit 5 test class with Kafka, optional Schema Registry, and ShadowTraffic containers wired together. Use when the user says "set up a Java TestContainers test with ShadowTraffic", "write a Java test that generates Kafka data", "create a TestContainers test for my Kafka consumer", "I want to test my Kafka consumer with synthetic data in Java", or "scaffold a ShadowTraffic Java test". Do NOT use for non-Java projects, standalone Docker setups (use kafka-shadowtraffic instead), or creating Kafka topics.
Review dead letter queue implementations for completeness using the Lenses MCP server. Checks DLQ topic existence, configuration, monitoring, metadata preservation, retry logic, reprocessing paths and connector DLQ alignment. Use when user says "review dead letter queues", "check DLQ setup", "DLQ audit" or asks about error handling, message failures or reprocessing. Do NOT use for reprocessing DLQ messages or managing consumer offsets.
Generate a ShadowTraffic configuration to populate a Kafka topic with realistic synthetic data. Discovers the target topic, its key and value schemas, and the correct serializers from the live cluster via any attached Kafka MCP server, then writes a ready-to-run `shadowtraffic-config.json` and Docker command. Use when the user says "populate my Kafka topic with test data", "set up ShadowTraffic for topic X", "generate synthetic events into my topic", "I need fake data flowing into Kafka", "seed my topic with data", or "mock data for my Kafka topic". Do NOT use for creating topics, reviewing schemas, or building Kafka consumers.
Generate and validate Pangolin Newt blueprint configurations in YAML or Docker Labels format. Use when creating Pangolin resource configurations, proxy resources, client resources, authentication settings, or Docker Compose blueprints.
Create new GitLab stack projects from templates with proper directory structure, git configuration, validation hooks, and documentation. Use when initializing new Docker stack projects that follow GitLab stack patterns.
Manages Docker secrets for GitLab stack projects, ensuring secrets are never in .env or docker-compose.yml, properly stored in ./secrets directory, and securely integrated with Docker secrets. Use when users need to create secrets, migrate from environment variables, validate secret configuration, audit secret usage, or ensure secrets are never committed to git.
Comprehensive Docker and Docker Compose validation following best practices and security standards. Use this skill when users ask to validate Dockerfiles, review Docker configurations, check Docker Compose files, verify multi-stage builds, audit Docker security, or ensure compliance with Docker best practices. Validates syntax, security, multi-stage builds, and modern Docker Compose requirements.
Validates GitLab stack projects before deployment, ensuring proper architecture patterns, directory structure, secrets management, .env configuration, and Docker best practices. Use when users ask to validate a stack, check stack configuration, verify stack architecture, audit stack setup, or ensure stack deployment readiness.
> Use when creating, deploying, or managing Dataverse web resources for model-driven apps. Covers JavaScript form scripts (OnLoad, OnSave, OnChange events), HTML dashboard pages, CSS styling, image resources, navigation/side panes, ribbon/command bar customization, "javascript form", "form script", "html dashboard", "ribbon command", "onload event", "onchange event", "onsave event", "formContext", "Xrm.WebApi", "web resource deployment", "dashboard page", "form event handler", "side pane", "command bar", "ribbon", "modal dialog", "navigation", "Xrm.App", "Xrm.Navigation", "business process flow", "bpf", "stage change".
> Use when developing, registering, or deploying Dataverse plugins (C# server-side extensions). Covers the IPlugin interface, execution pipeline stages, entity images, common patterns (auto-numbering, cascading updates, validation), and registration/deployment. "cascading update", "pre-operation", "post-operation", "plugin registration", "IPlugin", "execution pipeline", "plugin trace", "InvalidPluginExecutionException", "PreValidation", "PostOperation".
> Use when building, deploying, or using PowerApps Component Framework (PCF) controls. Covers field controls and dataset controls, React virtual controls, control lifecycle, "custom control", "component framework", "dataset control", "virtual control", "pac pcf", "pcf init", "pcf push", "ControlManifest", "StandardControl", "ReactControl", "updateView", "getOutputs".
Scan all unresolved Sentry errors, group by root cause, fix in batch with TDD, and resolve in Sentry after deploy. Use when the user says 'fix sentry errors', 'scan sentry', 'resolve sentry issues', 'fix all errors', 'sentry cleanup', or wants to proactively fix production errors from Sentry monitoring.
Pre-deployment validation of Cisco IOS/IOS-XE configuration — catching missing saves, mismatched ACLs, overlapping subnets, duplicate IPs, missing route-maps, and dangerous commands before they cause outages.
Design an end-to-end MotherDuck data pipeline. Use for ETL/ELT workflows -- choosing raw, staging, and analytics boundaries, bulk ingestion paths, transformation sequencing, dlt/dbt integration, publication targets, or whether DuckLake is actually required.
Deliver repeatable MotherDuck architectures across multiple clients. Use when a consultancy, agency, or multi-client product team needs to standardize isolation, provisioning, regional deployment, sharing boundaries, and client-specific exceptions across client engagements.
Design an end-to-end MotherDuck data pipeline. Use for ETL/ELT workflows -- choosing raw, staging, and analytics boundaries, bulk ingestion paths, transformation sequencing, dlt/dbt integration, publication targets, or whether DuckLake is actually required.
Deliver repeatable MotherDuck architectures across multiple clients. Use when a consultancy, agency, or multi-client product team needs to standardize isolation, provisioning, regional deployment, sharing boundaries, and client-specific exceptions across client engagements.
Create a new implementation plan file for new features, refactoring existing code or upgrading packages, design, architecture or infrastructure.
Update an existing implementation plan file with new or update requirements to provide new features, refactoring existing code or upgrading packages, design, architecture or infrastructure.
Produce a Competitive Analysis Pack (alternatives map, landscape, battlecards, monitoring plan).
Produce a Platform & Infrastructure Pack (capabilities plan, scaling triggers, execution roadmap).
Plan product launch/release: rollout/rollback plan, comms, monitoring, post-launch review. See also: launch-marketing (marketing side).
AWS CLI 操作
Azure CLI 操作
Ansible 自动化运维
CI/CD 流水线配置
Docker Compose 编排
Terraform 基础设施即代码
Docker 容器操作与管理
监控与告警
Docker 镜像管理
Docker 容器网络
Kubernetes ConfigMap 与 Secret
Kubernetes Deployment 管理
Helm 包管理
Kubernetes Pod 管理与调试
Kubernetes Service 与 Ingress
Kubernetes 故障排查
Linux system administration and monitoring
OpenClaw 运维与故障修复
OpenClaw 安装与部署
Defines metrics, events, dashboards, alerts, and SLOs to monitor production systems. Use after Gate 2 or with release-manager to ensure production observability.
Manages post-Gate-2 release activities with Agile V rigor. Rollout plans, rollback procedures, sign-off checklists. Use after Human Gate 2 for production deployment.
>- Hybrid fingerprint + LLM pipeline for bug classification, deduplication, and ticket generation. Normalizes CI logs, creates stable fingerprints, clusters near-duplicates, then uses LLM for severity classification and ticket writing. Includes bug reporting "failure analysis," "auto-classify," "CI failures," "bug report," "defect template." designing new tests from production telemetry — use observability-driven-testing.
>- Validate system resilience through controlled fault injection. Covers hypothesis-driven chaos experiments, failure injection types (network, service, infrastructure, dependency), LitmusChaos/Chaos Mesh/AWS FIS/Gremlin/toxiproxy tooling, automated abort gating, game day "resilience test," "game day," "failure recovery," "system reliability," "blast radius." designing new tests from production telemetry — use observability-driven-testing.
>- Design CI/CD pipelines that run test suites. Covers GitHub Actions and GitLab CI templates, parallelism and sharding, artifact management, flaky-test quarantine, test-result publishing, coverage quality gates, OIDC keyless deploy, and copy-paste workflows for Playwright, Jest, and multi-stage pipelines. "continuous integration," "test automation pipeline," "shard tests in CI." decisions and smoke-test checklists — use release-readiness; test-result dashboards and trend reporting — use qa-metrics.
>- Create and fill .agents/qa-project-context.md with the project's tech stack, test frameworks, CI/CD pipeline, environments, quality goals, risk areas, team structure, and conventions. This is the one file every other QA skill reads first, so they skip redundant discovery and give context-aware advice.