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
AWS SQS message queue service for decoupled architectures. Use when creating queues, configuring dead-letter queues, managing visibility timeouts, implementing FIFO ordering, or integrating with Lambda.
AWS Step Functions workflow orchestration with state machines. Use when designing workflows, implementing error handling, configuring parallel execution, integrating with AWS services, or debugging executions.
Use when creating a changeset, preparing a release, or bumping versions. Covers which packages to reference, how to write user-facing changeset descriptions, the release automation flow, and the npm/Docker version sync requirement. (project)
Use when you need to exercise a real, running Sandbox deployment via HTTP — for example to validate SDK changes against a live container, reproduce a user-reported issue, or experiment with the API (including FUSE bucket mounts) without spinning up `wrangler dev`. Documents the Sandbox bridge worker reachable via `SANDBOX_WORKER_URL` + `SANDBOX_API_KEY` when the host injects them.
> Set up and run ongoing competitive intelligence monitoring for a client. Tracks competitor content, ads, reviews, social, and product moves.
Fetch YouTube transcripts via APIFY API. Works from cloud IPs (Hetzner, AWS, etc.) by bypassing YouTube's bot detection. Free tier includes $5/month credits (~714 videos). No credit card required.
> on LinkedIn, new job postings, product usage patterns, funding announcements, and public company news. Produces a weekly expansion opportunity list with context and talk tracks. Chains web search, LinkedIn profile monitoring, and job posting detection.
CloudBase CLI (tcb, 云开发CLI, Tencent CloudBase命令行) resource management skill. This skill should be used when users need to deploy cloud functions, manage CloudRun apps, upload files to storage, query NoSQL/MySQL databases, deploy static hosting, set access permissions, or configure CORS/domains/routing via tcb commands. Also use for CI/CD pipeline scripting, batch operations, terminal-based CloudBase management, or when the user prefers CLI over SDK/MCP.
Use when users need to implement, integrate, debug, build, deploy, or validate a Web frontend after the product direction is already clear, especially for React, Vue, Vite, browser flows, or CloudBase Web integration.
> Interact with the kotlinx-rpc TeamCity CI/CD project using the `teamcity` CLI. Use this skill whenever the user wants to trigger builds, check build status, view build logs, monitor failures, manage the build queue, inspect agents, or do anything related to TeamCity CI. Also use it when the user mentions "TC", "TeamCity", "CI build", "run build", "build status", "build log", "trigger build", "check CI", or references a build configuration name or ID. Trigger even if the user doesn't say "TeamCity" explicitly -- if they ask about CI status, build failures, or want to run something on CI rather than locally, this is the right skill. Do NOT use this skill for local Gradle builds -- use `running_gradle_builds` or `running_gradle_tests` instead.
> Migrates .NET test projects from VSTest to Microsoft.Testing.Platform (MTP). Use when user asks to "migrate to MTP", "switch from VSTest", "enable Microsoft.Testing.Platform", "use MTP runner", or mentions EnableMSTestRunner, EnableNUnitRunner, or UseMicrosoftTestingPlatformRunner. discovered, --ignore-exit-code, TESTINGPLATFORM_EXITCODE_IGNORE), conditioning OutputType=Exe to test projects when centralizing MTP properties in Directory.Build.props. Supports MSTest, NUnit, xUnit.net v2 (via YTest.MTP.XUnit2), and xUnit.net v3 (native MTP). Covers runner enablement, CLI argument translation, xUnit.net v3 filter migration (--filter-class, --filter-trait, --filter-query), Directory.Build.props and global.json config, CI/CD pipeline updates, and MTP extension packages. xUnit.net v2 to v3 API migration, MSTest version upgrades, TFM upgrades, or UWP/WinUI test projects.
> Use when provisioning Azure resources for a Microsoft Agents SDK application — including creating an Azure Bot Service resource, setting up Entra app registrations, configuring identity credentials (UserManagedIdentity, FederatedCredentials, or ClientSecret), adding a Teams channel, running Bicep deployments for SSO, or setting up OAuth user sign-in connections via az CLI. Trigger even if the user doesn't say "provision" — use on requests like "set up my bot on Azure", "deploy my bot", "configure Azure for my bot", or "get Teams SSO working." Applies to all languages (dotnet, Node.js, Python).
Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.
Datadog API CLI with 49 command groups, 300+ subcommands. Skills and domain agents for monitoring, logs, APM, security, and infrastructure.
Integrate Core ML models in iOS apps for on-device machine learning inference. Covers model loading (.mlmodel, .mlpackage, .mlmodelc), predictions with auto-generated classes and MLFeatureProvider, compute unit configuration (CPU, GPU, Neural Engine), MLTensor, VNCoreMLRequest, MLComputePlan, multi-model pipelines, and deployment strategies. Use when loading Core ML models, making predictions, configuring compute units, or profiling model performance.
Implement, review, or improve maps and location features in iOS/macOS apps using MapKit and CoreLocation. Use when working with Map views, annotations, markers, polylines, user location tracking, geocoding, reverse geocoding, search/autocomplete, directions and routes, geofencing, region monitoring, CLLocationUpdate async streams, or location authorization flows. Also use when working with maps, coordinates, addresses, places, directions, distance calculations, or location-based features in Swift apps.
> Build, test, and deploy code-based Teams apps using the M365 Agents Toolkit CLI. local testing, Azure provision/deploy, Slack-to-Teams migration, cross-platform bot development, Block Kit to Adaptive Cards conversion, AI model integration (OpenAI/Azure/Anthropic/Bedrock). "message extension", "test with agents playground", "provision to azure", "deploy to azure", "migrate slack bot", "slack to teams", "convert block kit", "add azure openai to my bot"
This skill should be used when user asks to "query Azure resources", "list storage accounts", "manage Key Vault secrets", "work with Cosmos DB", "check AKS clusters", "use Azure MCP", or interact with any Azure service.
This skill should be used when user encounters "Azure MCP error", "Azure authentication failed", "az login required", "Azure CLI not found", or needs help configuring Azure MCP integration.
Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), feature flags (Flagship), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
This skill should be used when user asks to "deploy with Dokploy", "use Dokploy Cloud", "manage self-hosted Dokploy", "deploy Docker Compose on Dokploy", "manage Dokploy databases", "configure Dokploy domains", or "look up Dokploy CLI commands".
This skill should be used when user asks about "GCloud logs", "Cloud Logging queries", "Google Cloud metrics", "GCP observability", "trace analysis", or "debugging production issues on GCP".
This skill should be used when user asks to "deploy to Hetzner", "create Hetzner server", "manage Hetzner Cloud", "hcloud CLI", or works with Hetzner Cloud infrastructure including servers, networks, firewalls, load balancers, DNS zones, and volumes.
This skill should be used when user encounters "paper-search MCP error", "Docker not found", "Docker not running", "paper search not working", or needs help configuring paper search integration.
This skill should be used when setting up or managing Polar local development environment with Docker.
> Use when the user wants to provision infrastructure or third-party services caching", "give me a Postgres", "provision Redis", "I need hosting", "add a vector DB", "get me an API key for X", "get credentials for X", "sign up for a service", "set up monitoring", "show me the catalog", "what can I provision", "browse providers", "add an LLM provider", "configure model provider", "add email sending", "set up search", "add a message queue", "set up object storage", "add feature flags". Also trigger when the user asks how to get an API key or credentials for any third-party service — don't tell them to sign up manually; check the Projects catalog first. Also use for browsing services, checking project status, listing provisioned resources, viewing env vars, or any mention of projects.dev or adding/provisioning/connecting a cloud service.
Hit the Cloudflare REST API directly for operations that wrangler and MCP can't handle well. Bulk DNS, custom hostnames, email routing, cache purge, WAF rules, redirect rules, zone settings, Worker routes, D1 cross-database queries, R2 bulk operations, KV bulk read/write, Vectorize queries, Queues, and fleet-wide resource audits. Produces curl commands or scripts. Triggers: 'cloudflare api', 'bulk dns', 'custom hostname', 'email routing', 'cache purge', 'waf rule', 'd1 query', 'r2 bucket', 'kv bulk', 'vectorize query', 'audit resources', 'fleet operation'.
Scaffold and deploy Cloudflare Workers with Hono routing, Vite plugin, and Static Assets. Describe project, scaffold structure, configure bindings, deploy. Use whenever the user wants to create a Worker project, set up Hono on Cloudflare, configure D1 / R2 / KV / Queues bindings, or troubleshoot Worker export syntax, API route conflicts, HMR issues, or deployment failures.
Cloudflare D1 migration workflow: generate with Drizzle, inspect SQL for gotchas, apply to local and remote, fix stuck migrations, handle partial failures. Use when running migrations, fixing migration errors, or setting up D1 schemas.
Plan and execute entire application builds. Generates phased delivery roadmaps, then executes them autonomously — phase by phase, committing at milestones, deploying, testing, and continuing until done or stuck. Modes: plan (generate roadmap), start (begin executing), resume (continue from where you left off), status (show progress). Triggers: 'roadmap', 'start building', 'resume the build', 'keep going', 'build the whole thing', 'execute the roadmap', 'what phase are we on'.
Build MCP servers in Python with FastMCP. Define tools / resources / prompts, build the server, test locally, deploy to FastMCP Cloud or Docker. Use whenever the user mentions building an MCP server, exposing tools to LLMs, FastMCP, building a Claude integration, or troubleshooting FastMCP module-level server, storage, lifespan, middleware, OAuth, or deployment errors.
Install and configure NVIDIA NemoClaw (sandboxed OpenClaw agent platform) on Linux. Handles cloudflared tunnels, Docker cgroup fixes, OpenShell, sandbox creation, remote access via Cloudflare Tunnel, and known bug workarounds. Use whenever the user mentions installing NemoClaw, setting up OpenClaw, configuring an NVIDIA Spark or DGX for sandboxed agents, or troubleshooting NemoClaw deployment.
Use for agent-assisted Auto-FL optimization of an existing NVFLARE job in simulation, POC, or production. Do not use for code conversion, diagnosis-only work, or deployment setup.
Orchestrate iOS screenshot automation with xcodebuild/simctl for build-run, AXe for UI actions, JSON settings and plan files, Koubou-based framing (`asc screenshots frame`), and screenshot upload (`asc screenshots upload`). Use when users ask for automated screenshot capture, AXe-driven simulator flows, frame composition, or screenshot-to-upload pipelines.
Diagnose App Store submission blockers and operate review health with asc, including readiness validation, repair routing, status monitoring, cancellation, and retry decisions. Use when validation fails, a version is not in a valid state, review status is unclear or stuck, or a failed submission must be repaired and retried. For staging, upload, publication, and submission execution, use asc-release-flow.
> Create, wire, and publish Fabric Eventstream real-time streaming topologies via the Items REST API. Build definitions with 25 source types (Event Hubs, IoT Hub, CDC, Kafka, SampleData), 8 operators (Filter, Aggregate, GroupBy, Join, ManageFields, Union, Expand, SQL), 4 destinations (Lakehouse, Eventhouse, Activator, Custom Endpoint), DefaultStream/DerivedStream routing. **Invoke this filter operator, (4) add CDC source with Debezium flattening, (5) wire destinations, (6) modify/delete Eventstream definitions. Invoke before making "eventstream topology", "add source to eventstream", "add event hub source", "add filter operator", "eventstream filter", "eventstream destination", "CDC source", "eventstream operator", "eventstream definition", "update eventstream", "wire eventstream", "real-time ingestion pipeline", "eventstream topology deployment".
> Create and manage SQL database in Fabric items, author T-SQL DDL/DML with constraints, foreign keys, triggers, indexes, and vector columns. Deploy schema via SqlPackage (.dacpac/.bacpac), configure source control, CI/CD, and GraphQL APIs. "sql database in Fabric primary key default getdate sqlcmd", "create sqldb item", "create table sqldb ddl", "sqldb foreign key constraint", "sqldb stored procedure", "sqldb trigger create", "sqldb vector column", "SqlPackage dacpac deploy sqldb", "bacpac sqldb", "sqldb source control", "graphql api sqldb", "sqldb collation set", "sp_invoke_external_rest_endpoint".
> Execute authoring T-SQL (DDL, DML, data ingestion, transactions, schema changes) against Microsoft Fabric tables, (2) insert/update/delete/merge data, (3) run COPY INTO or OPENROWSET ingestion, (4) manage transactions or stored procedures, (5) perform schema evolution, (6) use time travel or snapshots, "create table in warehouse", "insert data via T-SQL", "load from ADLS", "COPY INTO", "run ETL with T-SQL", "alter warehouse table", "upsert with T-SQL", "merge into warehouse", "create T-SQL procedure", "warehouse time travel", "recover deleted warehouse data", "create warehouse schema", "deploy warehouse", "transaction conflict", "snapshot isolation error".
Onboard Azure Monitor / Application Insights observability data into Microsoft Fabric and guide business-impact insights by correlating telemetry with business data, Eventhouse external delta tables, verified schemas, an optional Real-Time (KQL) dashboard, and opt-in Operations Agent instructions. Triggers: onboard Azure Monitor into Fabric, correlate App Insights telemetry with business data, build a Real-Time KQL dashboard over telemetry, build an Operations Agent for business-impact alerting, determine if availability or latency impacted bookings orders or revenue, connect a Log Analytics workspace to Fabric.
> Port Azure HDInsight Spark clusters and Hive workloads to Microsoft Fabric. Replaces legacy HiveContext and standalone SparkContext constructors with the pre-instantiated SparkSession. Converts WASB and ABFS storage paths to OneLake abfss URLs via Shortcuts. Transforms Hive DDL (STORED AS ORC, external tables) to Delta Lake schemas inside Fabric Lakehouse. Maps Oozie workflow actions — spark, hive, shell, sqoop, coordinator — to Fabric Pipeline activities and schedule triggers. Introduces notebookutils for file and credential operations previously handled via (1) retire an HDInsight cluster and move to Fabric, (2) convert WASB paths or Hive DDL, (3) replace Oozie coordinators with Fabric Pipelines. "wasb to onelake", "hive ddl to delta", "oozie to fabric pipelines", "migrate an oozie action", "hive metastore lakehouse", "hdinsight spark migration".
> Migrate Synapse Data Factory pipeline artifacts to Microsoft Fabric Data Factory. pipeline activities, global parameters → Variable Libraries, SynapseNotebook activities → TridentNotebook. SSIS, SHIR-only, and Databricks activities are parked. (2) converting SynapseNotebook activities to TridentNotebook, (3) translating linked services to Fabric connections, (4) converting global parameters to Fabric Variable Libraries, (5) inlining dataset definitions into Fabric pipeline activities. "tridentnotebook pipeline activity", "global parameters to variable library", "linked service to fabric connection", "inline dataset fabric pipeline", "pipeline migration from synapse".
Production-ready scripts for Android app testing, building, and automation. Provides semantic UI navigation, build automation, log monitoring, and emulator lifecycle management. Optimized for AI agents with minimal token output.
Close out (or revisit) a Claude Managed Agent build — refresh the overview page, recap every primitive the founder now owns, show the run log and live status, suggest 1–2 tailored next upgrades, and sweep hygiene (sessions archived, key only in .env, no literal dates in deployment kickoffs). Use when the founder says "/wrap-up", "wrap up", "close it out", "where do things stand with my agent", or at the end of a /launch-your-agent build.
Create a new Azure SDK crate from a TypeSpec specification.
> Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, models rebuilt as dlnetwork for lean hardware, (2) direct C/C++ code generation from PyTorch and LiteRT models. Both patterns support all targets (Cortex-M/A/R, x86, GPU). neural networks; compress AI models for MCU; integrate AI in Simulink for system-level simulation; import PyTorch/ONNX/TensorFlow models for embedded deployment; optimize AI for resource-constrained hardware; or use loadPyTorchExportedProgram, loadLiteRTModel, importNetworkFromPyTorch, importNetworkFromONNX, importNetworkFromTensorFlow, importNetworkFromKeras, dlquantizer, exportNetworkToSimulink, or Embedded Coder with AI models.
> Generate C/C++ or CUDA code from an AI model (PyTorch, LiteRT) using MATLAB Coder or GPU Coder. Use when the user wants to integrate an AI model into an application with code generation as the end goal — generating MEX, CUDA MEX, static library, dynamic library, or executable — or using the model in Simulink for simulation and code generation. This skill currently documents the PyTorch ExportedProgram (.pt2) workflow via loadPyTorchExportedProgram; LiteRT is already supported by the product (loadLiteRTModel, R2026a+) but detailed guidance has not yet been added to this skill. invoke, codegen, MEX, CUDA, GPU, C, C++, deploy, AI model, deep learning model, LiteRT, TFLite, TensorFlow Lite, Simulink, slbuild, PyTorch ExportedProgram block, MATLAB Function block, dlosslib.
> Deploy MATLAB-generated code to embedded hardware using Embedded Coder. Use when configuring code generation for microcontrollers (STM32, Raspberry Pi, ARM Cortex), setting up PIL/SIL verification, disabling dynamic memory allocation, or configuring hardware-specific code generation settings. Covers ERT-based configurations, processor-in-the-loop testing, memory constraints, and the MEX→SIL→PIL verification progression.
Extract features from signals collected on rotating machinery components, including motors, pumps, fans, gears, bearings, and shafts. Signals can include vibration, electrical, or environmental sensor measurements. Use when developing and deploying condition monitoring and fault detection applications for rotating machinery, including industrial machines, electrical vehicles, internal combustion engines, turbines, and drive trains.