Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Cloud & DevOps
ArgoCD application review and troubleshooting via CLI. USE WHEN argocd app, sync status, health check, application diff, rollback, deployment history, GitOps troubleshooting. Provides commands for reviewing applications, comparing live vs desired state, and diagnosing sync failures.
Builds a serverless API and event-driven handlers over the local Azure SQL Database container using Azure Functions with the Azure SQL bindings. Use when a user wants "a serverless API over SQL", "Azure Functions with a database", "HTTP CRUD with SQL input/output bindings", "run code when a row changes", "react to inserts/updates/deletes", "event-driven on Azure SQL", or "SQL trigger function". The Azure SQL trigger binding (backed by Change Tracking) is the local event-driven mechanism; Change Event Streaming (CES) is cloud-only and cannot run against the local container. Triggers include "func start with SQL", "SqlTrigger", "SqlInput/SqlOutput binding", "local.settings.json SqlConnectionString". Reach for this when building serverless endpoints or change-driven logic on the local Azure SQL engine.
Provides an opinionated reference architecture for production Python web apps — FastAPI + async SQLAlchemy + Postgres, pydantic-settings config, Stripe billing, server-rendered Jinja or a decoupled SPA, deployed as a single Docker image on a managed platform via Terraform. Use when starting a new SaaS/web app, choosing a stack, structuring routers/services/models, wiring Stripe webhooks, protecting FastAPI docs or OpenAPI routes, setting up config/secrets, or deciding how to deploy.
Use CLI for Microsoft 365 (`m365`) to manage Microsoft 365 tenants, SharePoint, Entra ID, Teams, Outlook, Planner, Power Platform, Viva, Purview, and more from the command line. Activate when the user asks to manage, query, configure, or automate anything in Microsoft 365 — including SharePoint sites/lists/pages, Entra users/groups/apps, Teams channels/messages, Outlook mail/calendars, Planner tasks, Power Automate flows, Power Apps, Viva Engage/Connections, Purview labels, OneDrive, To Do, or Microsoft Graph extensions.
Provides comprehensive guidance for AWS EC2 including instance creation, configuration, security groups, and EC2 management. Use when the user asks about AWS EC2, needs to create EC2 instances, configure EC2, or manage AWS compute resources.
Provides comprehensive guidance for AWS CloudFormation including template creation, stack management, resources, and best practices. Use when the user asks about CloudFormation, needs to define AWS infrastructure, create CloudFormation templates, or manage AWS resources as code.
Container image security scanning, Dockerfile hardening, and ACR image management. Use when scanning container images for vulnerabilities with Trivy, hardening Dockerfiles (pinning versions, non-root runtime, SSH config), importing images to Azure Container Registry to avoid Docker Hub rate limits, or analyzing CVE findings. Also trigger when the user mentions image security, vulnerability scanning, CVE remediation, container hardening, Trivy scan, Docker security, or ACR image import — even if they don't explicitly say "container security".
Deploy, configure, and operate CrowdSec Security Engine, cscli, remediation components, acquisition pipelines, and AppSec WAF. Use for Linux or Docker installation, detection-to-blocking design, incident review, and safe changes. Do not use for generic firewall, Kubernetes, or reverse-proxy design; route those to the named platform skill and use this skill for CrowdSec integration.
Stand up your own fastCRW API server — single binary, Docker, or docker-compose with a bundled search-backend sidecar. Use when the user wants to run crw locally or on their own infra, configure renderers/proxies/ auth/LLM extraction, or understand the embedded vs proxy MCP modes.
Recommends the right Datadog products for a codebase and/or a stated goal — grounded in a tech-stack→product map and a use-case→product map built from Datadog product capabilities and common technology patterns. Recommendation only; no setup instructions. Use when a user asks which Datadog products fit their app, what to monitor, or which products serve a goal like security, cost, or LLM observability.
Use when working with the `dotenvx` env-var management tool — encrypting .env files, juggling multiple environments (.env.production / .env.staging / .env.ci), committing encrypted secrets to git with `.env.vault` / `.env.keys` / `.env.encrypted`, or wiring dotenvx into GitHub Actions. Trigger on `.env.vault` / `.env.keys` / `dotenvx` commands or symptoms (env-var leak risk, env per-stage management, encrypted secrets workflow) even if the user does not say "dotenvx" by name.
Fleet orchestration for distributed coding agents across Azure VMs. Invoked as `/fleet <command>`. Covers all fleet operations: status, scout, advance, adopt, watch, snapshot, dry-run, start, add-task, queue, auth, dashboard, tui, and more. Use when: user mentions fleet, agents, VMs, sessions, or asks "what are my agents doing".
Hardens Kubernetes RBAC by designing least-privilege Roles and ClusterRoles, auditing RoleBindings, eliminating cluster-admin sprawl, separating service accounts, and integrating an external OIDC identity provider. Use when tightening cluster access control, removing excessive ClusterRoleBindings, or hardening service-account permissions against escalation and lateral movement. Keywords: RBAC, Role, ClusterRole, RoleBinding, least privilege, service account, OIDC, cluster-admin. Do not use for discovering existing escalation paths - use auditing-kubernetes-rbac-privilege-escalation.
Configures Zero Trust Network Access (ZTNA) in AWS, Azure, and GCP using identity-aware proxies, micro-segmentation, and continuous verification with conditional access policies, replacing VPN-based access with BeyondCorp-style architectures. Use when replacing VPN remote access with identity-based controls, limiting lateral movement via micro-segmentation, or exposing cloud workloads to authenticated users without public internet exposure.
Convert operational incident and near-miss evidence into durable product, engineering, test, evaluation, and governance improvements with verified closure. Separate observed facts from causal hypotheses and unresolved uncertainty; map follow-up work across code, tests, skills, operations, product, and governance; track ownership, verification, and closure for every finding. Do not use to assign blame or produce a generic postmortem template; do not close learning because tickets were created — require evidence the intended change occurred.
Audit all Kafka topic configurations against production best practices using the Lenses MCP server. Checks replication factor, retention, partitions, compaction, naming conventions, orphaned topics and missing metadata. Use when user says "audit my topics", "check topic configs", "topic health check" or asks about retention, replication or partition settings. Do NOT use for creating, deleting or modifying topics.
Deploy and operate services on Lightning AI - run Docker containers or HuggingFace models (vLLM) behind autoscaled HTTPS endpoints, manage replicas, releases, endpoint auth, and logs. Use when the user wants to deploy an API, model server, or container to lightning.ai, or manage an existing deployment.
Run code in Lightning AI Sandboxes - fast, isolated ephemeral VMs with optional persistence, snapshots, custom images, Docker-in-sandbox (docker / docker compose), network egress policies, file I/O, public port URLs, and interactive PTY sessions. Use when the user wants to execute untrusted or experimental code safely, needs a throwaway cloud VM, wants to build/run containers or preview a containerized app, or asks about lightning.ai sandboxes or snapshots.
Operate, configure, benchmark, and troubleshoot llama.cpp across CPU, Metal, CUDA, HIP/ROCm, Vulkan, SYCL, and hybrid or multi-GPU systems. Use when installing or building llama.cpp, selecting or inspecting GGUF models, running llama-cli or bounded llama-completion, serving an OpenAI-compatible API with llama-server, tuning memory and performance, or diagnosing backend, context, template, and API failures. Do not use for model training or fine-tuning, general inference-framework selection, llama-cpp-python or other bindings, LlamaIndex, Ollama, or LM Studio operation.
Gather network configuration and connectivity details on Linux including interfaces, IP addresses, routing tables, DNS settings, and listening ports. Use when the user asks about IP configuration, network interfaces, connection issues, DNS resolution, open ports, routing, or network troubleshooting.
RouterOS command tree introspection via /console/inspect API. Use when: building tools that parse RouterOS commands, generating API schemas from RouterOS, working with /console/inspect, mapping CLI commands to REST verbs, traversing the RouterOS command hierarchy, or when the user mentions inspect, command tree, RAML, or OpenAPI generation for RouterOS.
Use when the user asks to "design an experiment", "build a predictive model", "run A/B test analysis", "perform causal inference", "engineer features", "evaluate model performance", "set up MLOps pipeline", "analyze time series", "calculate sample size", or "deploy a model to production". Expert data science covering statistical modeling, experimentation, causal inference, feature engineering, ML deployment, and advanced analytics with Python, R, and SQL.
Instrument an application with Sentry — detect the platform, install and initialize the SDK if needed, and wire up any signal — error monitoring, tracing/performance, logging, metrics, profiling, session replay, user feedback, cron check-ins, uptime monitors for the deployed app, and AI/LLM monitoring (agent runs, token cost, and conversations for OpenAI, Anthropic, Vercel AI, LangChain, Google GenAI, Pydantic AI, Laravel AI, Mastra, Eve, Flue, Pi Durable, the Cloudflare Agents SDK, and Workers AI). Use to add Sentry to a project or to capture more than errors.
Instrument an application with Sentry — detect the platform, install and initialize the SDK if needed, and wire up any signal — error monitoring, tracing/performance, logging, metrics, profiling, session replay, user feedback, cron check-ins, uptime monitors for the deployed app, and AI/LLM monitoring (agent runs, token cost, and conversations for OpenAI, Anthropic, Vercel AI, LangChain, Google GenAI, Pydantic AI, Laravel AI, Mastra, Eve, Flue, Pi Durable, the Cloudflare Agents SDK, and Workers AI). Use to add Sentry to a project or to capture more than errors.
Deploy general projects to remote servers. Automatically detects the project type (Node.js/Python/Rust/Go/static site), SSH configuration, environment setup, project upload, process management, Nginx reverse proxy, Cloudflare SSL, security hardening. Use when the user needs to deploy a project, launch a service, or configure a domain.
Corrects the wrong defaults a model has when standing up self-hosted SonarQube Server as a continuous gate on AI-generated code, verified against docs.sonarsource.com in July 2026 (Server 2026.3, LTA 2026.1). Use when configuring SonarQube, designing a quality gate, or wiring a scan step into CI for AI-assisted work. Covers the setups that run green while measuring almost nothing — the fudge factor skips duplication and coverage conditions below 20 new lines and is on by default; duplication is never measured on test code; no `new_cognitive_complexity` metric exists to gate on; `sonar.host.url` now defaults to sonarcloud.io rather than localhost; a shallow clone degrades new-code attribution to timestamps. Also covers AI Code Assurance — the project flag, gate qualification, the deprecated Copilot autodetection — and that Community Build cannot analyze pull requests at all. NOT for SonarQube Cloud, IDE connected mode, or authoring custom analyzer rules.
Use when deploying or operating SpacetimeDB on Maincloud or self-hosted infrastructure, configuring standalone services, rotating keys, viewing logs, filtering logs, or using PGWire. Triggers on: deploy, Maincloud, self-host, standalone, systemd, Nginx, key rotation, logging, spacetime logs, PGWire, psql.
Use this skill when developing applications with Supabase, running the Supabase CLI, designing migrations and RLS policies, testing database behavior, generating client types, deploying the official self-hosted Docker stack, or administering its Postgres, Auth, Storage, Realtime, Functions, API gateway, backups, upgrades, and security. Use it for managed and self-hosted projects. Do not use for generic PostgreSQL work with no Supabase services or conventions.
Design, implement, review, or improve operational reliability through service objectives, failure isolation, graceful degradation, recovery, observability, and incident readiness. Use when availability, resilience, dependency failure, disaster recovery, or operability is a primary concern. Do not use for ordinary error handling, a single unexplained bug, or speculative distributed-systems machinery.
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.