Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Cloud & DevOps
Operate, troubleshoot, secure, upgrade, and automate Kubernetes clusters and workloads safely across upstream Kubernetes, k3s, RKE2, MicroK8s, k0s, Talos, OpenShift/OKD, kind, Minikube, Rancher-managed clusters, EKS, AKS, and GKE. Use when a task involves kubectl, Kubernetes APIs, Pods, Deployments, StatefulSets, Services, Ingress or Gateway API, CRDs, RBAC, NetworkPolicy, storage, scheduling, autoscaling, cluster lifecycle, or the bundled agent-first k8s-cli. Do not use this skill for unrelated requests; route to the nearest named specialist.
Managing secrets (API keys, database credentials, certificates) with Vault, cloud providers, and Kubernetes. Use when storing sensitive data, rotating credentials, syncing secrets to Kubernetes, implementing dynamic secrets, or scanning code for leaked secrets.
Use Mergify CI commands to upload JUnit test results, detect git references, manage CI scopes, and retrieve merge queue metadata. ALWAYS use this skill when working with CI pipelines, test result uploads, quarantine, scopes detection, or merge queue CI context. Triggers on CI, JUnit, test results, quarantine, scopes, git refs, CI insights.
This skill should be used when the user asks to run isolated or untrusted code on Modal.com. PROACTIVELY activate for: modal.Sandbox, safe user code execution, coding playgrounds, named sandboxes, PTY sessions, filesystem snapshots, timeout and resource limits, egress policies, sandbox lifecycle cleanup, terminate(), and security review for code execution. Provides: sandbox security checklist, lifecycle and cleanup patterns, egress/resource-limit recipes, and snapshot/PTY usage examples.
This skill should be used when the user asks to work with Modal.com persistence or shared state. PROACTIVELY activate for: Modal Volumes, vol.commit, Dict, Queue, CloudBucketMount, S3 or GCS mounts, secret-backed storage credentials, model cache persistence, dataset staging, shared queues, distributed state, volume consistency, and storage troubleshooting. Provides: storage primitive selection matrix, commit/consistency patterns, mount configuration recipes, and troubleshooting checklists.
Modern Python patterns for Modal.com serverless platform. PROACTIVELY activate for: (1) Modal function deployment, (2) Type-safe Modal with Pydantic, (3) Async patterns in Modal, (4) GPU workloads (ML inference, training), (5) FastAPI web endpoints on Modal, (6) Scheduled tasks and cron jobs, (7) Modal Volumes and storage, (8) Testing Modal functions with pytest, (9) Modal classes and lifecycle methods, (10) Parallel processing with map/starmap. Provides: Type hints patterns, Pydantic integration, async/await patterns, pytest testing, FastAPI integration, scheduled tasks, Volume usage, cost optimization, and production-ready examples following Python 3.11+ best practices.
Administer and troubleshoot remote Linux, FreeBSD, NetBSD, OpenBSD, and macOS systems safely, one host or a fleet at a time. Use when a task requires SSH, Ansible, Paramiko, POSIX diagnostics, service management, software updates, system configuration, firewall changes, or evidence-led remote operations. Do not use for local-only desktop administration, container or cluster orchestration (route to kubernetes), or cloud consoles that expose no remote shell.
Server security audit and hardening. Scans for security issues such as SSH, firewall, port exposure, file permissions, and brute-force attacks, generates a report, and offers one-click fixes. Use when the user mentions server security, security audit, security check, or security hardening.
Build, review, migrate, and deploy Salesforce Multi-Framework React or Angular apps as UIBundle metadata. Use for uiBundles, ui-bundle.json, Data SDK and GraphQL integration, internal apps, Experience Cloud app containers, microfrontend embedding, ACC, localization, or UIBundle packaging. Also use when choosing Multi-Framework versus LWC. Pure LWC or generic Apex work does not require this skill.
Create, modify, and maintain Taskfiles following Task (https://taskfile.dev) best practices. Use when: (1) Creating new tasks or Taskfiles, (2) Modifying existing task definitions, (3) Adding new task includes, (4) Debugging task execution issues, (5) Questions about Taskfile syntax or patterns, (6) Running or understanding "task" commands, (7) Questions about available tasks or task namespaces. Triggers: "taskfile", "Taskfile.yaml", "task command", "task:", "create task", "add task", "task --list", "task tg:", "task inv:", "task wt:", ".taskfiles/", "how to run", "available tasks", "task syntax", "taskfile.dev" This skill covers the repository's specific conventions in .taskfiles/ and the root Taskfile.yaml.
Operate the observability stack that deploys as one unit: Prometheus scrape configuration, recording and alerting rules, relabeling, retention, and high availability; OpenTelemetry Collector pipelines (receivers, processors, exporters, sampling, trace/span correlation); and Loki ingest, LogQL, retention, and label design — with a bundled read-only telemetry-check script for Prometheus rule sanity and scrape-target reachability. Use when running, tuning, or troubleshooting a Prometheus, OpenTelemetry Collector, or Loki deployment, or reviewing the collection/ingest/retention layer, including bounded PromQL and LogQL query construction, semantic review, and no-data diagnosis. Do not use for observability strategy, SLI/SLO design, or paging policy (that is platform-engineering), Grafana dashboards, panels, and Grafana-side alerting (that is grafana), or Tempo/tracing operations, which remain deferred to a future named-tool skill.
Migrate from Twilio to Telnyx. Orchestrates a complete 6-phase migration: discovery, planning, setup, code migration, validation, and cleanup. Covers voice (TwiML to TeXML, Call Control API), messaging, WebRTC, SIP trunking, verify, fax, video, IoT, number lookup, and porting. Includes automated scanners, validation scripts, and integration tests.
vLLM Ascend plugin for LLM inference serving on Huawei Ascend NPU. Use for offline batch inference, API server deployment, quantization inference (with msmodelslim quantized models), tensor/pipeline parallelism for distributed serving, and OpenAI-compatible API endpoints. Supports Qwen, DeepSeek, GLM, LLaMA models with Ascend-optimized kernels.
Use this skill when controlling a VMOS Edge Android cloud phone through the Android Control API. If the current session also has `vmos-edge-container-api`, use `host_ip` and resolve the target `db_id` through the container APIs first. If this skill is installed alone, prefer `cloud_ip`; if `host_ip` and `db_id` are already known, the host route can also be used. If no IP is provided and local `cbs_go` is running, default `host_ip` to `127.0.0.1`.
Expert guidance on contributing to WendyOS: Yocto builds, agent internals, E2E testing, and system architecture. Use when developers mention: (1) building WendyOS images, (2) meta-wendyos layers or bitbake, (3) wendy-agent development or internals, (4) containerd or nerdctl on WendyOS, (5) E2E tests for wendy-agent, (6) Yocto recipes or bbappend files, (7) mDNS/Avahi service configuration, (8) device identity or UUID generation.
Deploy tRPC on WinterCG-compliant edge runtimes with fetchRequestHandler() from @trpc/server/adapters/fetch. Supports Cloudflare Workers, Deno Deploy, Vercel Edge Runtime, Astro, Remix, SolidStart. FetchCreateContextFnOptions provides req (Request) and resHeaders (Headers) for context creation. The endpoint option must match the URL path prefix where the handler is mounted.
Process, route, filter, and archive inbound email with Amazon SES Mail Manager. Use when building email ingress pipelines, spam/IP filtering, compliance archiving, SMTP relay forwarding, address allow/block lists, or any inbound email processing workflow. Covers ingress points, traffic policies, rule sets, relays, archives, and address lists.
Expert knowledge for Azure Durable Task development, including best practices, decision-making, architecture and design patterns, limits and quotas, configuration, integrations and coding patterns, and deployment. Use when building Durable orchestrations with Azure Storage/SQL/Netherite, versioning deployments, using instance APIs, or handling other Azure Durable Task-related development tasks. Not for Azure Functions (use azure-functions), Azure Logic Apps (use azure-logic-apps), Azure App Service (use azure-app-service), or Azure Service Fabric (use azure-service-fabric).
Constructs secure, efficient CI/CD pipelines with supply chain security (SLSA), monorepo optimization, caching strategies, and parallelization patterns for GitHub Actions, GitLab CI, and Argo Workflows. Use when setting up automated testing, building, or deployment workflows.
Use when YOU (the AI agent) are running on Windows OUTSIDE WSL (Git Bash/MSYS/PowerShell shell) and need to run ANY docker / docker compose command. Docker Desktop runs on the WSL2 engine, so commands must be re-issued INSIDE WSL via wsl.exe -- running them from the Windows shell on a network/SMB drive (Z:, UNC) corrupts bind-mount paths. Does NOT apply if your shell is already inside WSL. Triggers on: docker, docker compose, docker-compose, container, bind mount, volume, 'is a directory', mount source wrong, Windows + Docker Desktop, WSL.
Deploy an agent built with the eve framework (eve.dev / Vercel) onto Zavu, or import it straight from GitHub with `npx zavudev import`. Use this skill when the user has an eve-layout project (agent/instructions.md, agent/tools/*.ts) and wants it answering on Zavu's messaging channels, or asks whether an eve capability works on Zavu.
Complete fal.ai optimization system. PROACTIVELY activate for: (1) Queue vs run performance, (2) Parallel request batching, (3) Streaming for real-time UI, (4) WebSocket for interactive apps, (5) Model cost comparison, (6) Image size optimization, (7) Inference step tuning, (8) Webhook vs polling, (9) Result caching by seed, (10) Serverless scaling config. Provides: Parallel patterns, cost strategies, caching examples, monitoring setup. Ensures optimal performance and cost-effective usage.
Complete fal.ai serverless deployment system. PROACTIVELY activate for: (1) Creating fal.App class, (2) GPU machine selection (T4/A10G/A100/H100), (3) setup() for model loading, (4) @fal.endpoint decorators, (5) Persistent volumes for weights, (6) Secrets management, (7) Scaling configuration (min/max concurrency), (8) Multi-GPU deployment, (9) fal deploy commands, (10) Local development with fal run. Provides: App structure, Dockerfile patterns, deployment commands, scaling config. Ensures production-ready serverless ML deployment.
This skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before running analyses, training models, processing large datasets, or any task where resource constraints matter.
Helius Solana RPC and API expert. High-performance infrastructure for Solana including RPC nodes, DAS API for NFTs/tokens, LaserStream real-time streaming, webhooks, Priority Fee API, Enhanced Transactions, and ZK Compression. Triggers on Helius, Solana RPC, DAS API, Digital Asset Standard, NFT metadata, Solana webhooks, priority fees, LaserStream, ZK compression.
Queries Huawei Cloud Cloud Connect (CC) resources via hcloud CLI. Covers cloud connection instances (single + list), bandwidth packages (single + list), inter-region bandwidths (single + list), network instances (single + list), cloud connection routes (single + list), and cross-account authorisations (granted + received). No write operations. Use this skill when the user needs to inspect cross-cloud connectivity topology, check bandwidth package status, review inter-region bandwidth allocation, query network instances attached to a cloud connection, troubleshoot routing in Cloud Connect, or audit cross-account authorisation relationships (who authorised whom). Triggers: 云连接, CC, Cloud Connect, 带宽包, bandwidth package, 域间带宽, inter-region bandwidth, 网络实例, network instance, 路由查询, cloud connection route, 跨云网络, cross-cloud connectivity, 授权, authorisation, 被授权, permission, 跨账号, cross-account.
Use the LiveKit CLI to manage LiveKit Cloud projects, deploy agents, generate tokens, and configure telephony. Use this skill when working with the `lk` command-line tool for project setup, agent deployment, phone number management, or SIP configuration.
Use Mergify merge protections to control when PRs merge — PR dependencies (Depends-On header), delayed merges (Merge-After header), and scheduled freezes (CLI). ALWAYS use this skill when managing merge freezes, deployment windows, temporarily blocking merges, setting up PR dependencies, blocking a PR on another PR, coordinating cross-repo merges, scheduling a merge for a specific time, or adding Depends-On or Merge-After headers to PRs. Triggers on freeze, scheduled freeze, merge freeze, deployment freeze, halt merges, depends on, dependency, block merge, merge after, merge later, schedule merge, delayed merge, cross-repo, merge protection.
OpenClaw operations assistant. Use when the user mentions OpenClaw, 小龙虾, gateway, channel connections, failed message sending, unreachable services, log troubleshooting, or channel or Agent management. Prioritize status checks and fault triage; for high-impact operations such as restarting, repair, updates or configuration changes, explain them to the user before executing.
Define risk-scaled evidence packets and go/no-go/defer/exception launch gates with accountable owners. Do not use this skill for cross-domain production composition; use `production-excellence` for assembling migration, recovery, capacity, and incident evidence.
Helps with Prowler repository CI and PR gates (GitHub Actions workflows). Trigger: When investigating CI checks failing on a PR, PR title validation, changelog gate/no-changelog label, conflict marker checks, secret scanning, CODEOWNERS/labeler automation, or anything under .github/workflows.
Use when investigating and documenting a production incident, outage, data corruption event, or post-mortem — guides evidence collection during the investigation AND produces a rich, reproducible Root Cause Analysis report. Trigger on phrases like "write an RCA", "post-mortem for X", "document this incident", "what went wrong with...", "the pipeline broke yesterday, help me investigate", or any time the user is debugging a recently-resolved incident and wants a writeup. Also use proactively when the user finishes resolving an incident in-session and the resolution context is fresh — offer to capture it as an RCA before details fade.
Design, exercise, and evidence graceful degradation, disaster recovery, and restoration behavior across systems and dependencies. Covers failure-mode analysis, RTO/RPO decision records, restore testing, game days, failover drills, data integrity verification, and recovery communication. Do not use for live incident command or incident response; route to site-reliability-engineering for those. Do not use for infrastructure implementation details; route to platform-engineering.
Validates the user's environment for SageMaker AI operations — checks SDK version, AWS region, and execution role. Use when the user says "set up", "getting started", "check my environment", "configure SDK", or as the first step in any plan involving SageMaker/Bedrock training, evaluation, or deployment.
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.