Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Cloud & DevOps
Run bounded, evidence-driven training research through W&B Launch: assess project readiness, establish launchable code and queue capacity, smoke-test real jobs, execute serial trials, compare metrics, and persist resumable research state. Use when a coding agent is asked to autonomously test training hypotheses or tune a real W&B-tracked workload.
Miaoda (Spark/Miaoda) app development and hosting: app creation, local full-stack development, cloud generation and iteration, creative design (UI mockups / interactive prototypes / wireframes / landing pages / dashboards / slide decks / visual exploration), integration of AI capabilities, Feishu platform capabilities, or other external capabilities, log/Trace/monitoring metrics/PV/UV queries, environment variable management, app collaborators and collaboration permissions, app roles and members, and automation triggers (scheduled / record changes / Webhook / Feishu approval). Use when users want to develop or create a system, tool, platform, or app; develop locally or in the cloud; modify, deploy, publish, launch, or get a shareable link; build pages or websites with HTML and deploy them to Miaoda; design, create mockups, prototypes, wireframes, PPT/decks, or explore visuals; or mention Miaoda/Spark/Miaoda (app runtime domains such as *.aiforce.cloud), app databases, app file storage, open API Keys, visibility, app collaborators/development permissions, app roles/role members, production logs, API request volume, error counts, latency, traffic, environment variables, or setting up automation for Miaoda apps, including scheduled triggers or triggers after approval. Not responsible for ordinary cloud drive file uploads (lark-drive), Feishu document editing (lark-doc), or native slide creation (lark-slides).
Prepare and execute a Plannotator release—draft release notes with full contributor credit, bump versions across all package files, build in dependency order, and kick off the tag-driven release pipeline. Use this skill whenever the user mentions preparing a release, bumping versions, writing release notes, tagging a release, or publishing. Also trigger when the user says things like “let's ship”, “prep a release”, “what's changed since last release”, or “time to cut a new version”.
Use this skill when the user asks to "trigger a build", "check build status", "watch a build", "view build logs", "rebuild a build", "cancel a build", "list builds", "list jobs", "unblock a job", "download artifacts", "manage secrets", "create a pipeline", "list pipelines", "validate a pipeline", "copy a pipeline", "run a local agent", or "interact with Buildkite from the command line". Also use when the user mentions bk commands, bk build, bk job, bk pipeline, bk secret, bk artifacts, bk cluster, bk queue, bk package, bk agent, bk auth, bk config, bk use, bk browse, bk api, bk skill, or asks about Buildkite CLI installation, authentication, terminal-based Buildkite workflows, or command-line CI/CD operations.
Configures and runs Depot remote container builds using `depot build` and `depot bake`. Use when building Docker images, creating Dockerfiles with Depot, pushing images to registries, building multi-platform/multi-arch images (linux/amd64, linux/arm64), debugging container build failures, cancelling builds, configuring autoscaling, optimizing Dockerfile layer caching, using docker-bake.hcl or docker-compose builds, or migrating from `docker build` / `docker buildx build` to Depot. Also use when the user mentions depot build, depot bake, container builds, image builds, or asks about Depot's build cache, build parallelism, build autoscaling, or ephemeral registry.
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.
Find unused and rarely queried metrics in VictoriaMetrics using the metric_names_stats API, then suggest optimization actions (drop rules, relabel configs). Use this skill when the user wants to find unused metrics, identify wasted storage, optimize metric ingestion, reduce cardinality by dropping unneeded metrics, clean up scrape targets, or asks about which metrics are never queried. Also trigger when the user mentions "metric cleanup", "unused series", "what metrics can I drop", "metric optimization", "wasted ingestion", or wants to reduce VictoriaMetrics resource consumption by eliminating unnecessary metrics.
Use when setting up, verifying, or troubleshooting a custom Auth0 login domain (e.g. login.example.com). Covers CNAME setup, verification, TLS policy, Multiple Custom Domains, and Management API errors — even if the user just says "use my own domain for Auth0 login"
Telegram Bot development skill using the grammY framework, TypeScript, Drizzle ORM, Vitest testing, and Biome linting, deployed to Cloudflare Workers with a D1 database. Use for: (1) creating new Telegram Bot projects; (2) adding commands or features to existing Bots; (3) configuring Cloudflare Workers deployment; (4) setting up Drizzle + D1 database integration; (5) writing Bot test cases; (6) configuring Git hooks and GitHub Actions CI/CD
Create and query Alibaba Cloud alert rules via CLI. Supports CMS 1.0 cloud resource monitoring (ECS, RDS, SLB, etc.) and CMS 2.0 advanced monitoring (Prometheus, APM, UModel). Intent routing automatically selects the correct workflow based on alert type. Use this skill when users mention: create alert, setup monitoring, configure alarm, ECS/RDS/SLB alert, Prometheus alert, PromQL, K8s monitoring, APM alert, UModel alert, list alerts, query rules, 告警规则, 创建告警, 监控报警, Prometheus告警, 应用监控, 查看告警.
Push records from apps, services, devices, or scripts directly into Unity Catalog Delta tables with Zerobus Ingest: SDKs (Python, TypeScript, Go, Java, Rust, C++, .NET), REST, OTLP, MQTT, Arrow Flight, or Apache Kafka-compatible producer APIs, with no message bus to run. Use to stream events, telemetry, logs, IoT data, CDC, or columnar batches into Databricks in near real time; connect existing collectors and log shippers (OpenTelemetry, Debezium, Vector, Telegraf, Cribl); replace a message bus that only feeds the lakehouse; or debug Zerobus auth, schema, throughput, or delivery issues.
Use when deploying a Meteor 3 application. Triggers on meteor build, meteor deploy, Galaxy Push to Deploy, Galaxy Mode, Repository Mode, DEPLOY_HOSTNAME, Docker, Kubernetes, settings.json, METEOR_SETTINGS, MONGO_URL, MONGO_OPLOG_URL, ROOT_URL, PORT, HTTP_FORWARDED_COUNT, NODE_OPTIONS, health checks, pre-deploy commands, hot code push, --architecture os.linux.x86_64, --server-only, or a deployed Node.js version mismatch. Use this skill when the user asks about shipping the app, asks about production config, or asks about containerizing. For Cordova Android/iOS artifacts, signing, and native HCP compatibility use meteor-native; this skill owns the backend deployment.
Configures monitoring systems, implements structured logging pipelines, creates Prometheus/Grafana dashboards, defines alerting rules and instruments distributed tracing. Implements Prometheus/Grafana stacks, conducts load testing, performs application profiling and plans infrastructure capacity. Use when setting up application monitoring, adding observability to services, debugging production issues with logs/metrics/traces, running load tests with k6 or Artillery, profiling CPU/memory bottlenecks or forecasting capacity needs.
Check current Railway project status for this directory. Use when user asks "railway status", "is it running", "what's deployed", "deployment status", or about uptime. NOT for variables or configuration queries - use railway-environment skill for those.
Translates SQL queries, DDL schemas, and stored procedures from legacy database dialects (Teradata, Oracle, Redshift, Snowflake, SparkSQL, HiveQL) to BigQuery GoogleSQL using the BigQuery Migration Service (BQMS) MCP server. Use when translating legacy SQL queries, migrating schemas or metadata zip archives, or configuring BigQuery Migration Service (BQMS) YAML translation settings. Don't use for executing BigQuery queries or managing datasets and tables (use bigquery-basics), diagnosing runtime job errors (use bigquery-troubleshooting), or tuning slot reservations (use bigquery-optimization).
Configures an available test provider (e.g. Apex Unit Tests, Code Analyzer, Flow Tests, Provar) on a DevOps Center pipeline via the Connect API, after explicit user confirmation, so the provider's test suites become available for assignment to pipeline stages. Takes a pipelineId and a testProviderId. Use this skill when a provider is available on the pipeline but not yet configured and the user wants to enable it. TRIGGER when: the user wants to configure, enable, set up, or add a test provider on a pipeline, or wants a not-yet-configured provider's suites to become available. DO NOT TRIGGER when: re-syncing an already-configured provider to pick up new suites (use syncing-test-providers), or assigning existing suites to a stage (use managing-suite-assignments)
This skill should be used when working with GitHub CLI (gh) for any task including code search, workflow debugging, GitHub Pages deployment, or general GitHub operations. Use this skill for enhanced code search capabilities, analyzing failed workflow runs, managing GitHub Pages, or any gh command usage.
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.
Review Renovate bot PRs that update GitHub Actions dependencies. Verifies supply chain integrity by checking pinned commit SHAs against upstream tagged releases, reviews changelogs for breaking changes, and confirms compatibility with existing workflow configurations. Use when a Renovate PR updates GitHub Actions in .github/workflows/.
Query AlertManager via curl using the v2 API. Use when listing active/silenced alerts, creating/managing silences, or checking alert inhibition state. Triggers on: alertmanager, silences, silence alerts, alert filters, alert inhibition, alertmanager API, create silence, delete silence.
Set up Critical User Journey (CUJ) monitoring in bitdrift. Deploys a complete observability stack: path discovery (sankey), conversion funnel, completion rate SLO, key step duration alerting, session capture, and a two-tab dashboard. Trigger when a user wants to monitor a journey end-to-end, track conversion and drop-off, measure step duration, or set up SLOs on a business-critical flow such as checkout, onboarding, login, or search.
Volcengine AI MediaKit audio and video processing skill. Triggered when users need to process or edit audio/video content. After processing, it automatically checks task status and returns playback links for generated outputs. Core capabilities fall into five categories: 1) Video processing: multi-clip stitching, clip trimming, frame flipping, video speed adjustment, audio speed adjustment, image-to-video generation, audio-video composition, audio track extraction, and audio mixing; 2) Audio processing: vocal/accompaniment separation and audio noise reduction; 3) Video enhancement: comprehensive quality restoration, AI super-resolution, and intelligent frame interpolation; 4) AI content analysis: ASR speech-to-text, OCR text extraction, subtitle removal, subtitle embedding, intelligent scene slicing, portrait matting, green screen matting, media info query, and highlight extraction; 5) AI content generation: comic style transfer, AI video translation, AI drama recap narration, and AI drama script restoration. Trigger keywords: video stitching, video trimming, video editing, video speed change, video flipping, image to video, audio-video composition, audio extraction, mixing, vocal separation, background sound separation, audio denoise, denoise, AI super-resolution, super resolution, quality restoration, quality enhancement, intelligent frame interpolation, video frame interpolation, frame rate increase, speech recognition, ASR, OCR, text extraction, subtitle removal, subtitle erasure, add subtitle, embed subtitle, scene segmentation, scene slicing, portrait matting, green screen, highlight, comic style, video translation, drama recap, drama narration, drama script, script restoration, media info. Not applicable to pure text generation, real-time streaming processing, video understanding/analysis (except supported AI features), or AI generative video creation without source media inputs.
This skill deploys frontend and full-stack projects to EdgeOne Makers (Tencent EdgeOne). Trigger this skill whenever deployment is part of the task — whether as the primary intent or a secondary step. Examples: "deploy my app", "publish this site", "push this live", "create a preview deployment", "deploy to EdgeOne", "ship to production", "go live", "release", "publish a new version", "redeploy", "上线", "发布", "发一版", "重新部署", "搭建并部署", "开发并上线", "build and deploy", "create and deploy". Also trigger for login-free deployment and project claiming: "deploy without login", "no account yet", "anonymous deploy", "claim project", "claim my deployment", "免登录部署", "匿名部署", "还没有账号", "认领项目". Also trigger when any agent is about to execute `edgeone makers deploy` or `edgeone makers deploy` commands — the skill contains critical rules for parsing deploy output and presenting access URLs. Do NOT trigger for post-deployment runtime errors (e.g. CORS issues, 500 errors after deploy — use makers-env-adaption / makers-recipes for troubleshooting).
Huawei Cloud CCE (Cloud Container Engine) cluster lifecycle management skill using hcloud CLI (KooCLI) for Huawei Cloud API calls and kubectl cce plugin for Kubernetes node operations (cordon/uncordon/drain/status). Use this skill when the user wants to: (1) create, delete, hibernate, or awake CCE clusters, (2) list clusters and query cluster/node/nodepool/addon information, (3) manage node pools (create, delete, resize), (4) manage nodes (create, delete, cordon, uncordon, drain), (5) manage addons (install, uninstall, update), (6) bind/unbind cluster EIP for public access, (7) get cluster kubeconfig. Trigger: user mentions "CCE cluster", "create cluster", "delete cluster", "node pool", "node management", "hibernate cluster", "awake cluster", "addon", "kubeconfig", "EIP binding", "CCE 集群", "创建集群", "删除集群", "节点池", "节点管理", "休眠集群", "唤醒集群", "插件", "kubeconfig", "EIP 绑定"
Initialize or repair SigNoz MCP server configuration for Agent Plugins v1, Claude Code, Codex, Cursor, VS Code/GitHub Copilot, Claude Desktop, Gemini CLI, Devin CLI, Grok Build, Windsurf, Zed, Antigravity CLI, OpenCode, or another MCP client. Use this skill before any SigNoz docs, query, dashboard, alert, or view workflow when `signoz_*` tools are unavailable, or when the user says "setup SigNoz MCP", "configure SigNoz plugin", "wrong region", "change SigNoz region", "MCP auth failed", or asks to connect SigNoz Cloud or a self-hosted MCP endpoint, even if they do not mention the plugin.
Design and operationalize SRE dashboards that surface reliability, latency, error, saturation, and capacity signals across services. Use when building observability views for SLOs, incident response, and executive reliability reporting.
Manage Alibaba Cloud DataAnalysisGBI via OpenAPI/SDK. Use whenever the user needs DataAnalysisGBI resource lifecycle operations, configuration changes, status inspection, or troubleshooting for analytics service workflows.
Query Coralogix continuous-profiling data with the `cx profiling` CLI — find which services use the most CPU or memory, which profile types a service has, what profiles can be filtered by, when usage spiked and which pod or version caused it, and which code paths and functions a service spends its CPU or memory on (flame graphs). Use when the user asks "which services use the most CPU", "top memory consumers", "what is service X spending CPU on", "hot functions", "flame graph for a service", "why is this service using so much CPU", "memory allocations by function", "CPU spike by pod", "which version increased CPU", "continuous profiling", "profiling data", or wants to explore profiles of a service. For how much CPU or memory a service or pod uses and whether it is saturated, use `cx-service-catalog` instead.
Design distributed systems, define architecture for scalability and reliability, or create system design documents. Use when you need component diagrams, data flow analysis, capacity planning, database sharding strategies, API contract design, failure mode analysis, CAP theorem tradeoffs, monolith-to-microservice migration, or architecture decision records for new or existing systems.
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.
Use when deploying or managing Kubernetes workloads. Invoke to create deployment manifests, configure pod security policies, set up service accounts, define network isolation rules, debug pod crashes, analyze resource limits, inspect container logs, or right-size workloads. Use for Helm charts, RBAC policies, NetworkPolicies, storage configuration, performance optimization, GitOps pipelines, and multi-cluster management.
Guide for using the Pinecone CLI (pc) to manage Pinecone resources from the terminal. The CLI supports all index types (standard, integrated, sparse) and all vector operations—unlike the MCP, which only supports integrated indexes. Use for batch operations, vector management, backups, namespaces, CI/CD automation, and full control over Pinecone resources
Elite Talos Linux expert specializing in immutable Kubernetes OS, secure cluster deployment, machine configurations, talosctl CLI operations, upgrades, and production-grade security hardening. Expert in Talos 1.6+, secure boot, disk encryption, and zero-trust infrastructure. Use when deploying Talos clusters, configuring machine configs, troubleshooting node issues, or implementing security best practices.
Plans and builds end-to-end Fabric data platforms on the Bronze, Silver, and Gold medallion pattern: ingestion to analytics, PySpark and Delta layers, pipeline orchestration, per-layer Spark tuning, Materialized Lake View versus notebook choices for Silver and Gold, and Direct Lake handoff. Use for layered architecture design, planning and recommendations. For questions over an existing Power BI report use fabriciq.
Create HTML system architecture diagrams — microservice maps, dependency graphs, deployment topologies, data ownership maps, integration diagrams. Useful during incidents, design reviews, onboarding, and capacity planning. Use whenever the user wants to visualize, document, or explain how a system fits together — across services, regions, queues, caches, databases, or organizational boundaries. Reach for this whenever the explanation would otherwise involve sentences like "service A talks to service B which writes to queue C".
Designs distributed system architectures, decomposes monoliths into bounded-context services, recommends communication patterns, and produces service boundary diagrams and resilience strategies. Use when designing distributed systems, decomposing monoliths, or implementing microservices patterns — including service boundaries, DDD, saga patterns, event sourcing, CQRS, service mesh, or distributed tracing.
Designs and implements production-grade ML pipeline infrastructure: configures experiment tracking with MLflow or Weights & Biases, creates Kubeflow or Airflow DAGs for training orchestration, builds feature store schemas with Feast, deploys model registries, and automates retraining and validation workflows. Use when building ML pipelines, orchestrating training workflows, automating model lifecycle, implementing feature stores, managing experiment tracking systems, setting up DVC for data versioning, tuning hyperparameters, or configuring MLOps tooling like Kubeflow, Airflow, MLflow, or Prefect.
Create Railway projects, services, and databases with proper configuration. Use when user says "setup", "deploy to railway", "initialize", "create project", "create service", or wants to deploy from GitHub. Handles initial setup AND adding services to existing projects. For databases, use railway-railway-database skill instead.
Expert knowledge for Azure Networking development including troubleshooting, best practices, decision making, architecture & design patterns, security, and configuration. Use when designing VNets/VWAN, load balancers, firewalls/WAF, DDoS protection, or Virtual Network Manager policies, and other Azure Networking related development tasks. Not for Azure Virtual Network (use azure-virtual-network), Azure Virtual Network Manager (use azure-virtual-network-manager), Azure Virtual WAN (use azure-virtual-wan), Azure Network Watcher (use azure-network-watcher).
Designs cloud architectures, creates migration plans, generates cost optimization recommendations, and produces disaster recovery strategies across AWS, Azure, and GCP. Use when designing cloud architectures, planning migrations, or optimizing multi-cloud deployments. Invoke for Well-Architected Framework, cost optimization, disaster recovery, landing zones, security architecture, serverless design.
Alibaba Cloud SLS (Simple Log Service) index configuration manager skill. Use this skill to help users inspect, create, update, or delete a Logstore index, generate an index configuration from user-provided structured log samples, and optimize an existing index configuration for given query/SQL workloads, write throughput, and storage cost — all through the aliyun CLI. Triggers: "SLS 索引", "索引配置", "create index", "update index", "delete index", "generate index", "optimize index", "全文索引", "字段索引", "log index config", "aliyun sls index".
Configures Neon Serverless Driver for Next.js, Vercel Edge Functions, AWS Lambda, and other serverless environments. Installs @neondatabase/serverless, sets up environment variables, and creates working API route examples with TypeScript types. Use when users need to connect their application to Neon, fetch or query data from a Neon database, integrate Neon with Next.js or serverless frameworks, or set up database access in edge/serverless environments where traditional PostgreSQL clients don't work.
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.