Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Cloud & DevOps
Expert knowledge for Azure Information Protection development including best practices, decision making, configuration, and deployment. Use when choosing Azure RMS vs AD RMS, deploying RMS connectors, migrating keys/policies, or configuring MSIPC clients, and other Azure Information Protection related development tasks. Not for Azure Key Vault (use azure-key-vault), Azure Security (use azure-security), Azure Defender For Cloud (use azure-defender-for-cloud).
Expert knowledge for Azure Lab Services development, including troubleshooting, best practices, decision-making, architecture and design patterns, limits and quotas, security, configuration, integrations and coding patterns, and deployment. Use when configuring lab plans, VM templates or schedules, VNet-integrated labs, GPU or nested virtualization, Canvas or Teams integration, and other Azure Lab Services development tasks. Not for Azure DevTest Labs (use azure-devtest-labs), Azure Virtual Machines (use azure-virtual-machines), or Azure Virtual Desktop (use azure-virtual-desktop).
Expert knowledge for Azure Partner Solutions development, including troubleshooting, architecture and design patterns, security, configuration, and integration and coding patterns. Use when integrating Confluent/MongoDB via Service Connector, managing Datadog/Dynatrace/Elastic/New Relic, or Palo Alto Cloud NGFW, and for other Azure Partner Solutions development tasks. Not for Azure Industry (use azure-industry), Azure Managed Applications (use azure-managed-applications), Azure Lighthouse (use azure-lighthouse), or Azure Oracle (use azure-oracle).
Expert knowledge for Azure Stack Edge development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when deploying IoT Edge modules, GPU/Kubernetes apps, DeepStream workloads, Arc GitOps, or local ARM integrations, and other Azure Stack Edge related development tasks. Not for Azure IoT Edge (use azure-iot-edge), Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Kubernetes Service Edge Essentials (use azure-aks-edge-essentials), Azure Virtual Machines (use azure-virtual-machines).
Builds remote MCP (Model Context Protocol) servers on Cloudflare Workers with tools, OAuth authentication, and production deployment. Generates server code, configures auth providers, and deploys to Workers. Use when: user wants to "build MCP server", "create MCP tools", "remote MCP", "deploy MCP", add "OAuth to MCP", or mentions Model Context Protocol on Cloudflare. Also triggers on "MCP authentication" or "MCP deployment". Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
Upgrades Google Cloud Armor security policies from OWASP CRS 3.0 and 3.3 to OWASP CRS 4.22. Preserves signature opt-in and opt-out lists, translates evaluatePreconfiguredExpr to native evaluatePreconfiguredWaf dictionary parameters, remaps signature IDs to v042200, drops retired signature IDs, and updates structured preconfiguredWafConfig fine-tuning exclusions. Evaluates operational risk (High Breaking Change, Medium Attention Required, Low Clean Upgrade), including Method Enforcement breaking changes (PUT/PATCH/DELETE blocking) and sensitivity coverage expansions. Supports both in-place rule upgrades and smooth preview mode deployments with priority spacing and a 200-rule quota guardrail. Use when a user or agent needs to audit, upgrade, or transition Cloud Armor WAF rules to CRS 4.22. Don't use for non-WAF Cloud Armor rules (IP rate-limiting, geo-blocking, reCAPTCHA) or AWS/Azure WAF migrations.
Use cmux Cloud machines through the CLI. Use when the user says cmux cloud, cloud VM, cloud machine, cmux vm, Base workspace, machines panel, run/exec on a cloud machine, cloud agent, vm snapshot/fork/restore, push/pull files to a VM, open a port or desktop on a machine, or notify from inside a VM.
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.
You are a debugging expert specializing in setting up comprehensive debugging environments, distributed tracing, and diagnostic tools. Configure debugging workflows, implement tracing solutions, and establish troubleshooting practices for development and production environments.
Creates, validates, formats, and modifies Infrahub schema YAML files — nodes, generics, attributes, relationships, and extensions. Also checks the Infrahub Marketplace for an existing published schema to reuse before modelling a domain from scratch. TRIGGER when: designing data models, adding schema nodes, validating schema definitions, planning schema migrations, modifying or extending an existing schema, changing an attribute or relationship on a node kind, debugging why a schema fails to load or a migration is rejected, checking the marketplace for an off-the-shelf schema, modeling file objects / attachments / uploads (PDFs, images, certificates, documents), formatting schema files, canonicalising schema key order, or running `infrahubctl schema format` (including as a CI gate). DO NOT TRIGGER when: populating or editing object data files (use infrahub-managing-objects), writing checks/generators/transforms, querying live data, planning an Infrahub version upgrade (use infrahub-planning-upgrades)
Creates, modifies and debugs Infrahub transforms that convert data into JSON, text, CSV, or device configs using Python or Jinja2 templates, with YAML-driven tests. TRIGGER when: building config generation, data export, format conversion, Jinja2 templates, artifact pipelines, writing or running tests for a transform, modifying or extending an existing transform or template, debugging why a transform renders the wrong output or an artifact fails to generate. DO NOT TRIGGER when: designing schemas, writing validation checks, creating generators, querying live data
Modern DevOps and CI/CD bash automation patterns with containers and cloud (2025). PROACTIVELY activate for: (1) writing CI/CD scripts (GitHub Actions, GitLab CI, Azure DevOps), (2) container-aware shell scripting (detecting containers, Kubernetes pods), (3) cloud provider helpers (AWS CLI, Azure CLI, gcloud), (4) blue-green and canary deployments via bash, (5) writing idempotent rollback scripts, (6) integrating with Docker/Compose from bash, (7) cross-environment variable management, (8) build matrix orchestration. Provides: copy-pasteable CI snippets, container detection helpers, cloud CLI wrappers, deployment orchestration patterns, and idempotent rollback templates
Migrates Synapse Data Factory pipelines to Fabric Data Factory, turning linked services into Fabric connections, inlining datasets into activities, converting global parameters to Variable Libraries, and mapping SynapseNotebook to TridentNotebook. Use for pipeline JSON. For Synapse Spark notebook code use synapse-migration.
Expert knowledge for Azure Data Share development, including troubleshooting, decision making, security, configuration, and deployment. Use when estimating Data Share costs, securing invitations, fixing share errors, configuring datasets, or deploying across regions, and other Azure Data Share related development tasks. Not for Azure Data Box (use azure-data-box-family), Azure Data Explorer (use azure-data-explorer), Azure Data Factory (use azure-data-factory), Azure Open Datasets (use azure-open-datasets).
Expert knowledge for Azure Dedicated HSM development, including troubleshooting, decision-making, architecture and design patterns, security, integration and coding patterns, and deployment. Use when sizing HSM clusters, configuring ExpressRoute IP SKUs, securing VNets, planning HSM retirement, or scripting CLI/PowerShell provisioning, and for other Azure Dedicated HSM development tasks. Not for Azure Cloud Hsm (use azure-cloud-hsm), Azure Key Vault (use azure-key-vault), or Azure Payment Hsm (use azure-payment-hsm).
Expert knowledge for Azure HPC Cache development, including troubleshooting, best practices, decision-making, architecture and design patterns, limits and quotas, security, configuration, integrations and coding patterns, and deployment. Use when configuring HPC Cache namespaces, NFS or Blob targets, client access, data ingestion scripts, cache failover, and other Azure HPC Cache development tasks. Not for Azure Managed Lustre (use azure-managed-lustre), Azure NetApp Files (use azure-netapp-files), Azure Batch (use azure-batch), or Azure Virtual Machines (use azure-virtual-machines).
Expert knowledge for Azure Large Instances development, including troubleshooting, limits and quotas, and integrations and coding patterns. Use when configuring Epic SKUs, sizing volume groups, tuning EHR storage, resolving Epic–ALI connectivity or performance issues, and other Azure Large Instances development tasks. Not for Azure Baremetal Infrastructure (use azure-baremetal-infrastructure), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Machine Scale Sets (use azure-vm-scalesets), or Azure HPC Cache (use azure-hpc-cache).
Expert knowledge for Azure Operator Service Manager development, including troubleshooting, best practices, security, configuration, and integration and coding patterns. Use when onboarding CNFs/VNFs with Helm, managing ACR artifacts, configuring cluster registry, Private Link, or RBAC, and for other Azure Operator Service Manager development tasks. Not for Azure Operator Insights (use azure-operator-insights), Azure Operator Nexus (use azure-operator-nexus), Azure Resource Manager (use azure-resource-manager), or Azure Networking (use azure-networking).
Expert knowledge for Azure Oracle development, including troubleshooting, security, and integration and coding patterns. Use when configuring Oracle TDE with Azure Key Vault, Exadata log export, Azure Monitor, Sentinel, or PPGs, and for other Azure Oracle development tasks. Not for Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines), or SAP HANA on Azure Large Instances (use azure-sap).
Expert knowledge for Microsoft Planetary Computer Pro development, including troubleshooting, decision-making, limits and quotas, security, configuration, integrations and coding patterns, and deployment. Use when working with GeoCatalog or STAC APIs, configuring collections or tiles, securing access, integrating QGIS or ArcGIS, troubleshooting ingestion, and other Microsoft Planetary Computer Pro development tasks. Not for Azure Maps (use azure-maps), Azure Open Datasets (use azure-open-datasets), or Azure Data Explorer (use azure-data-explorer).
Expert knowledge for Azure Relay development, including troubleshooting, security, configuration, and integrations and coding patterns. Use when configuring Hybrid Connections, WCF relays, Entra ID or SAS authentication, Private Link, .NET or Node.js Relay clients, and other Azure Relay development tasks. Not for Azure Service Bus (use azure-service-bus), Azure Event Hubs (use azure-event-hubs), Azure Web PubSub (use azure-web-pubsub), or Azure Application Gateway (use azure-application-gateway).
Build and deploy applications on inference.sh. Use when getting started, understanding the platform, creating apps, configuring resources, or needing an overview of inference.sh app development. Supports both Python and Node.js. Triggers: inference.sh app, belt app, inf.yml, inference.py, inference.js, deploy app, app development, build app, create app, GPU app, VRAM, app resources, app secrets, app integrations, multi-function app
Docker on Windows with Git Bash / MINGW path conversion. PROACTIVELY activate for: (1) Docker commands failing on Windows Git Bash with path errors, (2) volume mount path conversion (-v $(pwd):/app), (3) MSYS_NO_PATHCONV and MSYS2_ARG_CONV_EXCL workarounds, (4) double-slash escapes (//c/foo) for MINGW, (5) docker-compose volume mounts on Windows, (6) WSL2 vs Hyper-V backend path interop, (7) line-ending issues in mounted scripts (CRLF vs LF), (8) UNC path limitations. Provides: MSYS path-conversion explainer, copy-pasteable env-var workarounds, double-slash recipes, line-ending fixes, and compose-mount patterns for Windows
Expert-level Linkerd service mesh management, traffic control, reliability, and production operations. Use when the user mentions service mesh, Kubernetes, microservices, mTLS, or observability, or when the task involves Linkerd Architecture, Mesh Injection, Traffic Management, or Reliability Features.
Designs and implements CI/CD pipelines and automated deployments for Magento 2. Use when setting up deployment pipelines, automating deployments, managing infrastructure, or implementing DevOps practices. Masters containerization, orchestration, and scalable deployment strategies.
ShellCheck validation as a non-negotiable 2025 workflow practice. PROACTIVELY activate for: (1) running ShellCheck on bash scripts, (2) interpreting and fixing ShellCheck warnings (SC2086, SC2068, SC2155, SC2295, SC2327, SC2328, SC2294), (3) integrating ShellCheck into CI (GitHub Actions, Azure DevOps, pre-commit), (4) per-line and per-file disable directives (when justified), (5) shellcheck-rc and project configuration, (6) ShellCheck v0.11.0 new checks, (7) suppressing false positives correctly. Provides: ShellCheck install/CI setup, common warning catalog with fixes, CI workflow templates, and a quality gate pattern that fails builds on regressions.
Azure Kubernetes Service (AKS) Automatic mode and 2025 platform features. Proactively activate for: (1) AKS Automatic (managed Kubernetes, zero operational overhead), (2) Karpenter-based autoscaling on AKS, (3) NodePool CRD usage, (4) HPA, VPA, and KEDA on AKS, (5) workload identity and Microsoft Entra integration, (6) AKS billing models (Automatic vs. Standard), (7) AKS 2025 cluster defaults (RBAC, Azure CNI overlay, Cilium), (8) AKS upgrade and version management, (9) GitOps on AKS (Flux, ArgoCD), and (10) AKS observability (Azure Monitor for containers, Managed Prometheus). Provides an AKS Automatic vs. Standard comparison, Karpenter setup, workload identity recipes, KEDA scaler patterns, and an end-to-end AKS Automatic deployment guide.
Inspect ECS instance health, detect anomalies in memory, disk, CPU, load, and resource leaks, and automatically trigger deep diagnosis when critical memory issues are detected. Suitable for routine inspections, troubleshooting, and risk warning scenarios. Trigger keywords: SysOM, inspection, instance diagnosis, memory_usage_rate, memory usage.
Expert knowledge for Azure AI Immersive Reader development including best practices, limits & quotas, security, configuration, and integrations & coding patterns. Use when tuning read-aloud/translation, storing user prefs, Entra auth setup, JS SDK integration, or language support, and other Azure AI Immersive Reader related development tasks. Not for Azure AI Language (use azure-language-service), Azure AI Speech (use azure-speech), Azure Translator (use azure-translator), Azure AI services (use microsoft-foundry-tools)
Expert knowledge for Azure Import Export development including troubleshooting, limits & quotas, and security. Use when setting CMK via Key Vault, checking drive limits, validating prerequisites, or debugging Import/Export job failures, and other Azure Import Export related development tasks. Not for Azure Data Box (use azure-data-box-family), Azure Blob Storage (use azure-blob-storage), Azure Files (use azure-files).
Expert knowledge for Azure Open Datasets development including limits & quotas. Use when handling non-Spark dataset downloads, throttling behavior, quota limits, retry logic, or rate-limit workarounds, and other Azure Open Datasets related development tasks. Not for Azure Data Explorer (use azure-data-explorer), Azure Synapse Analytics (use azure-synapse-analytics), Azure Databricks (use azure-databricks), Azure Machine Learning (use azure-machine-learning).
Expert knowledge for Azure Osconfig development including troubleshooting, security, configuration, and integrations & coding patterns. Use when running OSConfig via IoT for commands/networking, SSH Posture Control, agent health, or Windows security baselines, and other Azure Osconfig related development tasks. Not for Azure Update Manager (use azure-update-manager), Azure Automation (use azure-automation), Azure Policy (use azure-policy).
Expert knowledge for Azure Payment Hsm development including troubleshooting, best practices, decision making, architecture & design patterns, security, and configuration. Use when configuring Payment HSM VNets/peering, FastPath, payShield Manager access, SKUs, HA/DR topologies, or traffic routing, and other Azure Payment Hsm related development tasks. Not for Azure Cloud Hsm (use azure-cloud-hsm), Azure Dedicated HSM (use azure-dedicated-hsm), Azure Key Vault (use azure-key-vault), Azure Security (use azure-security).
Azure Container Apps with GPU support, serverless capabilities, and Foundry Models. Proactively activate for: (1) Container Apps GPU (serverless GPU workloads), (2) Container Apps with Dapr integration, (3) scale-to-zero AI workloads, (4) Container Apps Jobs (one-shot, scheduled, event-driven), (5) Container Apps Foundry Models integration, (6) revisions and traffic splitting, (7) custom domains and managed certificates, (8) ingress and authentication, (9) Container Apps Environment configuration, and (10) Workload Profiles (Consumption vs. Dedicated). Provides a GPU SKU reference, scale rule examples (HTTP, KEDA), Dapr building-block recipes, traffic-splitting patterns, and end-to-end serverless GPU deployment.
Configure a DataHub instance to load and display a Micro Frontend (MFE) app. Use when the user wants to register an MFE with DataHub, add an MFE to the nav sidebar, set up MFE config for local dev or production/k8s, or troubleshoot MFE loading issues.
ADF + Microsoft Fabric / OneLake 2025 integration. Proactively activate for: (1) the Fabric Lakehouse connector in ADF, (2) the Fabric Warehouse connector in ADF, (3) OneLake shortcuts and cross-workspace data, (4) Invoke Pipeline activity for cross-platform orchestration (ADF -> Fabric, Fabric -> ADF), (5) copying data between ADF and Microsoft Fabric workspaces, (6) authenticating with Fabric workspace identity, (7) cross-platform parameter passing, and (8) hybrid ADF + Fabric pipeline patterns. Provides Fabric connector setup, Invoke Pipeline templates, OneLake shortcut patterns, and ADF-to-Fabric migration guidance
Hardens the Docker daemon (dockerd) through /etc/docker/daemon.json with user namespace remapping, TLS client authentication, seccomp profiles, and CIS Docker Benchmark controls such as icc, no-new-privileges, and live-restore. Use when securing a Docker host's daemon to prevent privilege escalation, breakout, or lateral movement, or when auditing daemon settings against CIS requirements. Keywords: dockerd, daemon.json, userns-remap, no-new-privileges, icc, live-restore, TLS socket. Do not use for hardening images and per-container runtime flags - use hardening-docker-containers-for-production.
Huawei Cloud UCS (Ubiquitous Cloud Native Service) policy governance and compliance management skill using hcloud CLI. Use this skill when the user wants to: (1) manage UCS policy instances — create, update, query, or delete; (2) manage UCS policy definitions — query or list; (3) enable or disable policies on clusters or fleet groups; (4) check policy enforcement job status; or (5) audit fleet compliance and review policy enforcement status. Trigger: user mentions “UCS policy”, “UCS 策略”, “UCS governance”, “UCS 治理”, “UCS compliance”, “UCS 合规”, “policy instance”, “策略实例”, “policy definition”, “策略定义”, “enable policy”, “启用策略”, “disable policy”, “禁用策略”, “fleet compliance”, “舰队合规”, “policy audit”, “策略审计”, “UCS 策略管理”, “UCS 合规治理”, “policy governance”, or “策略治理”.
Creates, modifies and debugs Infrahub check definitions — Python validation logic, GraphQL queries, and YAML-driven tests for proposed change pipelines. TRIGGER when: writing validation checks, creating Python checks, building data quality guards for proposed changes, writing or running tests for a check, modifying or extending an existing check, debugging why a check fails, passes when it should not, or flags the wrong nodes. DO NOT TRIGGER when: designing schemas, querying live data, building transforms or generators
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.