Skills
96,770 packaged capabilities and playbooks for agents. Install any of them with one command.
Cloud & DevOps
Reduce your Grafana Cloud bill by attributing spend to teams and reducing telemetry volume. Covers FOCUS-compliant billing dashboards, cost-attribution labels in Alloy, Adaptive Metrics (cardinality reduction), Adaptive Logs (drop/sample), Adaptive Traces (tail sampling), usage alerts, and an optimization checklist. Use when investigating a high Grafana Cloud bill, attributing observability cost to a team or service, reducing active series / log bytes / trace spans, or setting up usage / quota alerts — even when the user says “our Grafana bill is too high”, “who’s burning the most metrics”, “drop debug logs”, “sample our traces”, or “alert me before we hit quota” without naming Cost Management
Manage a fleet of Grafana Alloy collectors with Fleet Management — author Alloy pipelines once, target them via attribute matchers (`env="production"`, regex `region=~"us-.*"`), push remotely via OpAMP without restarting collectors. Covers pipeline create / update / matcher RPCs, collector attribute API, `remotecfg` bootstrap block (standalone + Helm), pre-deploy `alloy fmt` validation, the local Alloy UI at port 12345 for component health, and post-deploy `REMOTE_CONFIG_STATUS_APPLIED` verification. Use when standing up a Cloud Alloy fleet, pushing a config change to 200 collectors, hunting why one collector shows `REMOTE_CONFIG_STATUS_FAILED`, validating River syntax before saving, or wiring `discovery.kubernetes` → `prometheus.remote_write` — even when the user says "configure Alloy", "remote config the collectors", "push pipeline", "OpAMP", "collector is unhealthy", or "manage agent config centrally" without naming Fleet Management.
Inspects Filestore capacity and utilization on Google Cloud, evaluates storage scaling rules, and performs capacity autoscaling (scale UP for low free space or scale DOWN for cost optimization). Use when monitoring Filestore instance headroom, resizing instance shares, configuring automated growth/shrink thresholds (custom thresholds apply globally across projects in session memory), or preventing out-of-space outages. Don't use for Cloud Storage (GCS) buckets, Persistent Disk block storage, or NetApp Volumes.
Send telemetry data to Grafana Cloud — metrics via Prometheus remote write or OTLP, logs via Loki push or Alloy, traces via OTLP to Tempo, and profiles via Pyroscope. Covers Alloy-based pipelines, direct SDK/agent integrations, cloud integrations catalog, and credentials management. Use when connecting an application or infrastructure to Grafana Cloud, setting up data ingestion, configuring remote write, or choosing between ingestion methods
Route alerts, run on-call rotations, and drive incidents in Grafana IRM / OnCall — integrations (Alertmanager / Grafana Alerting / generic webhook / PagerDuty), Jinja2 routing + grouping templates, escalation chains (wait → notify schedule → notify team → webhook → auto-resolve), schedules (web + iCal + Terraform `grafana_oncall_schedule`), Slack chatops with Acknowledge/Resolve/Silence, and the P1-P4 incident lifecycle. Use when wiring Alertmanager to OnCall, deciding which team gets paged, building rotations from a Google Calendar / iCal, hooking up Slack notifications, or declaring an incident from an alert — even when the user says "page the platform team on critical alerts", "send Prometheus alerts to Slack", "set up our on-call rota", "escalation policy", or "auto-resolve when the alert clears" without naming OnCall / IRM. Heads up — OnCall OSS is in maintenance mode (archived March 2026); Grafana Cloud users should use IRM
Set up, configure, and troubleshoot Grafana Cloud integrations for AWS, Azure, and other cloud providers. Use when the user asks to connect AWS CloudWatch, set up Azure Monitor, configure Confluent Cloud observability, install a Grafana integration, set up hosted exporters, use AWS Firehose for CloudWatch logs, or troubleshoot a cloud integration. Triggers on phrases like "AWS CloudWatch", "Azure Monitor", "Confluent integration", "cloud integration", "hosted exporter", "AWS Firehose", "install integration", "cloud metrics", or "cloud logs"
Generates valid Cloud Monitoring ListTimeSeries requests and aggregation specifications from metric descriptors and resource parameters. Use when asked to create, generate, format, or build ListTimeSeries requests, JSON payloads, filter expressions, or aligner/reducer aggregations for Cloud Monitoring metrics and charts. Don't use for metric discovery or metric selection.
Provides guidance for authoring Apache Airflow DAGs in Managed Service for Apache Airflow (MSAA; formerly Cloud Composer). Covers environment context discovery, Airflow 2 vs 3 compatibility, authoring best practices, and local/remote validation processes. Use when creating or extending an Airflow DAG. Don't use when authoring Python code unrelated to Airflow DAGs
Find the Prometheus metrics that drive your Grafana Cloud bill. `dpm-finder` is a Grafana Professional Services CLI that ranks metrics by Data Points per Minute (DPM) with per-label-set breakdown, optional `--cost-per-1000-series` pricing, and a Prometheus-exporter mode. Use when investigating high Grafana Cloud spend, hunting noisy / high-cardinality metrics, comparing pre/post recording-rule cardinality, or feeding cost data into dashboards — even when the user says "why is my Mimir bill so high?", "find the biggest metrics", "cardinality offenders", or "optimize Prometheus cost" without naming dpm-finder
Manage Grafana Cloud accounts — organizations, stacks, RBAC roles and assignments, SSO/SAML/OAuth/GitHub auth, service accounts for CI/CD, user invites, team membership, and API-driven provisioning. Creates stacks via the Cloud API, mints service-account tokens, applies role assignments, configures SSO providers, and provisions teams/folders/dashboards via Terraform. Use when managing Grafana Cloud access, configuring SSO/SAML/OAuth, setting up service accounts for Terraform/CI/CD, assigning RBAC roles, inviting users, managing multiple stacks or organizations, provisioning cloud resources via API or Terraform, or auditing admin actions — even when the user says "set up SSO", "create a stack", "make a service account", or "onboard a team" without explicitly saying "admin".
Use when tasks involve Xget URL rewriting, registry/package/container/API acceleration, integrating Xget into Git, download tools, package managers, container builds, AI SDKs, CI/CD, deployment, self-hosting, or adapting commands and config from the live README `Use Cases` section into files, environments, shells, or base URLs.
Turn on AI + ML features in Grafana Cloud — Grafana Assistant (NL → PromQL/LogQL/TraceQL, dashboard build, incident investigation, MCP integration), Dynamic Alerting (Prophet forecasting + DBSCAN outlier detection), Sift (8-analysis automated root-cause), Knowledge Graph + RCA Workbench, and the LLM Plugin (OpenAI / Anthropic / Azure / Ollama / vLLM / LiteLLM). Use when you want anomaly alerts without static thresholds, natural-language querying, automated incident investigation, dashboards generated from a sentence, or a managed LLM proxy for plugins — even when the user says "alert when something looks weird", "explain this PromQL", "find the root cause", "make this a dashboard", or "wire Claude into Grafana" without naming any of these products.
Set up private network connectivity to Grafana Cloud — AWS PrivateLink, Azure Private Link, GCP Private Service Connect, and Private Data Source Connect (PDC). Provisions VPC endpoints, private endpoints, or PSC forwarding rules per signal type (metrics / logs / traces / profiles); wires Alloy to push to the private DNS endpoint instead of the public one; verifies private DNS resolution + endpoint approval state. Use when sending telemetry to Grafana Cloud without traversing the public internet, eliminating cloud egress costs, meeting PCI-DSS / HIPAA / data-residency compliance, configuring PDC for private data-source queries, or connecting AWS / Azure / GCP workloads to Grafana — even when the user says "stop paying egress", "keep our telemetry off the public internet", or "PCI compliance for Grafana" without naming PrivateLink.
Control LaunchDarkly feature flag targeting including toggling flags on/off, percentage rollouts, targeting rules, individual targets, and copying flag configurations between environments. Use when the user wants to change who sees a flag, roll out to a percentage, add targeting rules, or promote config between environments.
Configures AWS Transit Gateway: creating a hub and attaching VPCs, segmenting traffic with route tables, centralizing egress and inspection through a hub (appliances or a Gateway Load Balancer endpoint), forcing east-west traffic between VPCs through AWS Network Firewall, connecting on-premises networks over the transit-gateway side of a Site-to-Site VPN or Direct Connect attachment (including ECMP to aggregate bandwidth across multiple VPN tunnels), peering transit gateways across Regions, migrating from a VPC peering mesh, and routing IP multicast. Applicable when connecting many VPCs through one router, isolating environments, forcing VPC-to-VPC traffic through a central Network Firewall, reaching on-premises over the hub, linking Regions, or moving off a peering mesh. Not applicable for single-VPC routing, VPC peering between two VPCs (vpcpeering skill), Direct Connect gateway or virtual interface setup (directconnect skill), or Route 53 DNS work.
Guides the end-to-end AWS resilience lifecycle integrating Resilience Hub v2, Fault Injection Service, and Application Recovery Controller. Covers the Define → Test → Operate workflow: from policy creation through failure mode assessment, to FIS experiment validation, to ARC operational controls. Applicable when the user wants a complete resilience strategy, needs to connect findings to experiments to controls, or is planning a resilience program. Also applicable for the meta question of whether marking NGRH findings as resolved is enough, whether they are "done" after resolving findings, or how to validate findings before resolving them. Not applicable for resolving or remediating a specific individual finding (see resilience-hub-failure-mode-assessment), or when a single service is explicitly named (e.g. "what FIS experiment should I run").
Automated semantic versioning and release workflow for Claude Code plugins. Handles version increments across package.json, marketplace.json, plugin.json manifests, build verification, git tagging, GitHub releases, and changelog generation. NPM publishing (so `npx [email protected]` resolves) is handed off to the human maintainer, who raised npm security.
Configures AWS Direct Connect: choosing a connection model (dedicated, hosted, or a link aggregation group) and completing the cross connect; creating private, public, and transit virtual interfaces and bringing up BGP; reaching many VPCs through a Direct Connect gateway including cross-account transit gateway associations; encrypting traffic with MACsec or a private IP Site-to-Site VPN; making the connection resilient and tuning failover; managing link aggregation groups; SiteLink; and migrating from a virtual private gateway to a transit gateway. Use when the user wants a private, consistent network link between a data center and AWS, or operates an existing Direct Connect setup and needs to extend, encrypt, or harden it. Routes to the right per-task procedure in references. Do NOT use for transit gateway route tables and attachments (transitgateway skill), Site-to-Site VPN without Direct Connect (sitetositevpn skill), or Route 53 DNS routing (route53 skill).
Turbo pipeline YAML reference and architecture guide. Covers: YAML field syntax (start_at, from, version, primary_key), source/transform/sink configuration, validation errors, resource sizing (xs–xxl), architecture decisions (dataset vs kafka, streaming vs job, fan-out vs fan-in, sink selection, pipeline splitting). Triggers on: 'what does field X do', 'what fields does a postgres sink need', 'what resource size', 'should I use kafka or dataset', 'how to structure my pipeline'. For writing transforms, use /turbo-transforms. For end-to-end building, use /turbo-builder.
Build and deploy new Goldsky Turbo pipelines: requirements, dataset selection, YAML, validation, and deployment. Use for 'build a pipeline', 'index X on Y chain', or moving chain/contract data into Postgres, MySQL, ClickHouse, Kafka, Pub/Sub, S3, SQS, or webhooks. Also use for data goals such as Polymarket fills/positions/PnL, prediction markets, stablecoin or circulating supply, proof of reserves, sanctions/AML transfer monitoring, deposit detection, CCTP burns/mints, cross-chain settlement, payment reconciliation, wallet history streamed into the user's own database, token holder registries, tokenized equities/RWA, and wash-trading detection. A REST lookup of one wallet's balances or transfers is /feeds, not a pipeline, and so is a read of Polymarket activity, positions or balances. Debug existing pipelines with /turbo-doctor; look up syntax with /turbo-pipelines.
Set up Goldsky CLI authentication and project configuration. Use this skill when the user needs to: install the goldsky CLI (what's the official install command?), run goldsky login (including when the browser opens but 'authentication failed'), run goldsky project list and see 'not logged in' or 'unauthorized', switch between Goldsky projects, check which project they're currently authenticated to, or fix 'unauthorized' errors when running goldsky turbo commands. Also use for 'walk me through setting up goldsky CLI from scratch for the first time', and when they just installed Goldsky and say 'Set it up and help me get started'. If any other Goldsky skill hits an auth error, redirect here first.
Diagnose and fix broken Goldsky Turbo pipelines interactively. Triggers on: pipeline in error state, stuck starting, connection refused, not getting data, duplicate rows, missing fields, slow backfill, or any named pipeline misbehaving. Runs logs/status commands, identifies root cause, and offers fixes. For CLI syntax or error pattern lookup without an active problem, use /turbo-operations instead.
Use this skill when a user wants to store, manage, or work with Goldsky secrets — the named credential objects used by pipeline sinks. This includes: creating a new secret from a connection string or credentials, listing or inspecting existing secrets, updating or rotating credentials after a password change, and deleting secrets that are no longer needed. Trigger for any query where the user mentions 'goldsky secret', wants to securely store database credentials for a pipeline, or is working with sink authentication for PostgreSQL, Neon, Supabase, ClickHouse, Kafka, S3, Google Cloud Pub/Sub, Elasticsearch, DynamoDB, SQS, OpenSearch, or webhooks.
Operate InstaCloud infrastructure with the `insta` CLI: create projects, add postgres/storage/compute services, deploy apps, create disposable branch environments (isolated DB + storage + compute per branch), schedule recurring HTTP calls (cron jobs) against a service or an external URL, bind service credentials into compute env, wire user secrets into `.env`, run multiple agents each in their own branch, handle governance approvals, check metrics/logs/usage, and promote branches to main. Use this skill when working in an InstaCloud-managed project (a `.insta/` dir or the `insta` CLI), when the user mentions InstaCloud or insta, AND when they ask to deploy an app, need a database/backend/object storage, want a scheduled or recurring task, want preview or per-agent sandbox environments, want branchable infrastructure, want to migrate an existing app in from Heroku / Railway / Fly / Render, or mention agent setup or MCP — even if they don't say "InstaCloud" explicitly. Also covers the insta-cloud remote MCP server (insta_* tools) and the self-hosted insta-oss runtime (same CLI, local daemon)
Manages the end-to-end lifecycle of on-demand, temporary access using Privileged Access Manager (PAM). Use when a user asks to create, read, update, or delete PAM entitlements, request temporary access, or approve/deny pending PAM grants. Do NOT use for permanent IAM policy bindings, troubleshooting IAM permission errors, or general Google Cloud resource provisioning.
Turbo pipeline operations reference — lifecycle commands (pause, resume, restart, delete), pipeline states, checkpoint behavior, streaming vs job-mode differences, CLI syntax for `inspect`/`logs`, TUI shortcuts, and error pattern lookup. Triggers on: 'how do I pause/restart/delete', 'will deleting lose my data', 'what does this error mean', 'inspect TUI shortcuts'. For interactive diagnosis of a broken pipeline, use /turbo-doctor.
Create Sentry alerts using the workflow engine API. Use when asked to create alerts, set up notifications, configure issue priority alerts, or build workflow automations. Supports email, Slack, PagerDuty, Discord, and other notification actions.
Use this skill when the user asks about Goldsky Mirror pipelines — creating, deploying, operating, or troubleshooting Mirror. Triggers on: 'Mirror pipeline', 'goldsky pipeline apply', 'sync subgraph to database', 'mirror vs turbo', 'direct indexing', 'mirror pipeline YAML', 'mirror pipeline pause/stop/restart'. Also use this skill when the user wants to sync a Goldsky subgraph into a database or message queue — Mirror is the only pipeline product that supports subgraph sources. For new pipelines that don't need a subgraph source, the turbo-builder skill is usually a better fit. Do NOT trigger on 'goldsky turbo' commands or generic 'build a pipeline' requests without subgraph context — those belong to the turbo skills.
Diagnose and fix broken Goldsky Mirror pipelines. Use this skill whenever a Mirror pipeline is failing, stuck, terminated, won't start, is in a restart loop, or is blocked by an in-flight request. Also use it when the user mentions a specific Mirror pipeline name alongside a problem—even if they don't say “mirror” explicitly, if they're using `goldsky pipeline` commands (not `goldsky turbo`), this is the right skill. Runs CLI commands directly to check status, read errors, identify the root cause, and apply fixes. For YAML syntax or config reference, use /mirror instead. For turbo pipeline problems, use /turbo-doctor instead
Configures AWS Shield Advanced for enhanced Distributed Denial of Service (DDoS) protection: subscribing accounts and adding resource protections, enabling automatic application layer (layer 7) mitigation through AWS WAF, configuring health-based detection with Route 53 health checks, setting up Shield Response Team (SRT) access and proactive engagement, reviewing DDoS events and requesting cost protection credits, and aggregating resources into protection groups. Applicable when the user wants stronger DDoS protection for internet-facing resources (CloudFront, Application or Network Load Balancers, Elastic IP addresses, Global Accelerator, or Route 53 hosted zones), wants expert help during an attack, or wants to recover attack-driven scaling charges. Routes to the right per-task procedure in references. Not applicable for authoring AWS WAF rules (waf skill), creating Route 53 health checks (route53 skill), or org-wide Shield Advanced rollout with Firewall Manager (firewallmanager skill).
Teaches the fundamentals of Cloud Build on Google Cloud. Covers core concepts, API enablement, console navigation to the Build History page, and the end-to-end workflow for creating and manually running a basic build trigger. Do not use for managing private pools or complex pipeline architectures.
Processes GCP infrastructure design and deployment workflows within Application Design Center (ADC). Use when: - Designing GCP infrastructure with Terraform. - Validating local HCL. - Performing best-practice plan scans. - Importing templates to Application Design Center (ADC). - Deploying templates. - Troubleshooting deployment failures. Boundaries: - Only use for GCP-specific cloud infrastructure. - Only use for Terraform coding within the ADC context.
This skill should be used when the user asks to "find a dashboard", "search dashboards", "does a dashboard exist for X", "find widgets that query Y", "which dashboards use this field", "find a dashboard about errors", "look up dashboards by description", "search for existing monitoring dashboards", "find widgets that reference a field", or wants to discover existing Coralogix dashboards or widgets using natural-language or field-based search.
Configure and troubleshoot Goldsky Edge, Goldsky's managed EVM RPC endpoint service. Use for Edge RPC, Goldsky RPC endpoints, edge.goldsky.com, slow eth_getLogs, rate limits, hedged requests, flashblocks, HyperEVM system transactions, x402 pay-per-request RPC, pricing, the Edge dashboard, gs_edge_ keys, rpc-edge, and errors -32005/-32012/-32014/-32015/-32016. Covers resilient, low-latency EVM endpoints and provider comparisons. For self-hosted eRPC configuration, consult docs.erpc.cloud/llms.txt. To keep an existing provider and reduce its bill through caching, or for x-cache / x-edge-billable / goldsky boost, use /boost. Pipeline and Subgraph questions have separate skills
Implement Terraform Provider resources and data sources using the Plugin Framework: CRUD operations, schema design, plan modifiers and validators, not-found handling, waiters for eventually consistent APIs, import support, resource design principles, and required acceptance test coverage. Use when adding or changing a resource or data source, deciding whether an API concept should be a resource, wiring a resource to the provider's configured client, handling drift or resource-not-found, or reviewing a resource implementation before submission.
Provides comprehensive Turborepo monorepo management guidance for TypeScript/JavaScript projects. Use when creating Turborepo workspaces, configuring turbo.json tasks, setting up Next.js/NestJS apps, managing test pipelines (Vitest/Jest), configuring CI/CD, implementing remote caching, or optimizing build performance in monorepos
Designs chaos experiments, creates failure injection frameworks, and facilitates game day exercises for distributed systems — producing runbooks, experiment manifests, rollback procedures, and post-mortem templates. Use when designing chaos experiments, implementing failure injection frameworks, or conducting game day exercises. Invoke for chaos experiments, resilience testing, blast radius control, game days, antifragile systems, fault injection, Chaos Monkey, Litmus Chaos
Mounts Cloud Storage buckets on Google Cloud as a POSIX file system with Cloud Storage FUSE (gcsfuse). Use when interacting with gcsfuse or Cloud Storage FUSE mounts: decide whether FUSE, native gs:// reads, or Filestore/Managed Lustre fits a workload, deploy tuned mounts on GKE, Compute Engine, or Cloud Run, enable and size file, stat, and list caches, tune mount flags (--implicit-dirs) or config files, apply workload profiles, keep ML checkpointing safe (rename atomicity, hierarchical namespace/HNS, close-time finalization, concurrent writers), or diagnose slow training, low throughput, or bill spikes with gcsfuse metrics. Covers mount semantics, gcsfuse CLI and configs, GKE gcsfuse CSI driver (Workload Identity principal:// bindings, profile StorageClasses, sidecar sizing), and Cloud Run volume mounts. Don't use for bucket administration without a mount (google-cloud-storage-basics) or POSIX shared file systems (Filestore, Managed Lustre; use gke-storage).
Answers questions about Amazon Application Recovery Controller (ARC) Region switch including architecture, plans, execution blocks, workflows, triggers, active/active vs active/passive, cross-account support, recovery time, dashboards, and customer positioning. Applicable when users ask about ARC Region switch adoption, design, or troubleshooting.
Migrate a subgraph from The Graph to Goldsky as a drop-in replacement — no code changes required. Use this skill when the user wants to move, switch, port, or migrate a subgraph off The Graph (hosted service, Subgraph Studio, or the decentralized network) onto Goldsky, or when a subgraph endpoint they relied on (e.g. The Graph hosted service) was sunset. Triggers on: 'migrate from The Graph', 'move my subgraph to Goldsky', 'switch off The Graph', 'redeploy a TheGraph subgraph', 'my subgraph endpoint is gone', 'from-url', 'from-ipfs-hash', 'drop-in replacement for The Graph'. For diagnosing a subgraph that fails after migrating, use /subgraph-doctor. For building/authoring or general deploy/tag/endpoint reference, use /subgraph-builder.
Publish previews to a public URL, open-source projects to community GitHub, and list services (free or paid) on the Service Marketplace. Use when the user wants to share, publish, list, open-source, or monetize what they built (e.g. make this dashboard public, share my project, push to GitHub, 上架到服务市场, 上架付费服务, 提交审核).
Instruments assistant-ui AI SDK backend routes with Langfuse, LangSmith, or Helicone, and renders independent trace data with the experimental @assistant-ui/react-o11y SpanResource and SpanPrimitive APIs. Use it when traces are missing, serverless spans are dropped, an AI SDK call needs provider metadata, Helicone is not proxying a provider, or a trace tree or timeline needs rendering. For streaming transport use streaming, for initial application wiring use setup, for Assistant Cloud persistence use cloud, and for copied styled trace UI use elements
Safely simulates and applies Identity and Access Management (IAM) v1 (Allow) policy changes on Google Cloud. Uses the Policy Simulator to replay historical access logs against proposed policies and prevent breaking active workloads before applying changes. Use when simulating or applying IAM v1 allow policies across Projects, Folders, or Organizations. Don't use for analyzing IAM v2 deny policies, VPC Service Controls, or general policy troubleshooting.
Designs a resilience program: how to structure and standardize resilience policies across an organization, team, or portfolio (tiered policy model with availability/RTO/RPO targets and DR approach selection), and how often to run resilience activities (operational cadence). Applies when the user asks how to structure policies org-wide, what tiers/targets to set, which DR approach fits a tier, or how frequently to run assessments, FIS experiments, GameDays, or autoshift practice. Does not apply to creating or configuring a specific policy or resource for a single workload (use resilience-hub-getting-started), to step-by-step lifecycle execution (see aws-resilience-lifecycle), or to service-specific setup.
Guides an end-to-end data-warehouse migration to Amazon Redshift — discovery, schema/SQL/stored-procedure/macro/script conversion, data migration, validation, performance comparison, and reporting. Source-routed via `references/<source>/`; Teradata (Vantage) is the supported source; additional sources are added as their own `references/<source>/` sets. Text-only knowledge (no executable code) — the AI generates all execution at runtime. Applies when a user wants to migrate Teradata to Amazon Redshift, convert Teradata DDL/SQL/stored procedures/macros/BTEQ to Redshift/RSQL, or assess Teradata-to-Redshift migration complexity. Applies only to migrations targeting Amazon Redshift; migrations to other platforms (Snowflake, BigQuery, Databricks, etc.) are out of scope regardless of source. Does not cover general Redshift administration, performance tuning, or troubleshooting of existing Redshift clusters (no migration involved), or sources not listed under references/.
Authors and edits AWS Step Functions state machines: writes Amazon States Language (ASL) in JSONata, and chooses and structures state types (Task, Choice, Map, Parallel, Pass, Wait, Succeed, Fail). Covers ASL syntax, JSONata data transformation and variables, Retry/Catch error handling, service integrations (.sync, waitForTaskToken callbacks), Distributed Map for large-scale S3/CSV processing, saga/compensation patterns, Standard vs Express workflow choice, TestState API unit testing, and migrating state machines from JSONPath to JSONata. Use when the user is building, authoring, debugging, or migrating a Step Functions state machine or ASL definition, or orchestrating multi-step workflows with branching, retries, or human-approval callbacks, even if they don't say 'Step Functions.' Do NOT use for general Lambda function code, API Gateway, EventBridge wiring, or SAM/CDK application packaging
Sets up AWS Resilience Hub v2 from scratch: creates resilience policies with SLO targets, registers systems and user journeys, onboards services with input sources, and runs a first failure mode assessment. Applies when the user wants to get started with Resilience Hub v2, create a policy, onboard a service, or run an assessment — including creating one concrete policy with specific availability/RTO/RPO targets and a DR approach for a single service (even a tier-1 one). Does not apply to FIS experiments or ARC routing controls.
Runs and interprets AWS Resilience Hub v2 failure mode assessments. Covers starting assessments, understanding findings (severity, categories, recommendations), triaging by achievability, working with AI-generated service functions, and resolving findings. Applies when the user wants to run an assessment, review findings, or understand failure modes, or has a specific finding and asks how to resolve, remediate, or fix it. Does not apply to initial setup (use resilience-hub-getting-started) or FIS experiments.
Configures AWS Resilience Hub v2 for multi-account resilience management across an AWS Organization. Covers the per-service cross-account permission model, cross-account IAM roles, and centralized assessment from a single account. Applies when the user wants to set up org-wide resilience or assess workloads that span multiple AWS accounts.
Configure and troubleshoot Goldsky Boost, the free RPC caching CDN in front of a provider the user already pays for. Use for cutting RPC bills without migrating, connecting Alchemy/QuickNode/Infura upstreams, goldsky boost, edge.goldsky.com/boost, verification, cache hit rates, eth_getLogs forwarding, and x-cache / x-edge-billable / x-edge-source headers. Boost keeps the existing provider and forwards uncached requests. To replace a provider with Goldsky's managed RPC, use /edge. Pipeline, Subgraph, and Compose tasks have separate skills.
Configures AWS Application Recovery Controller (ARC) for operational resilience: routing controls with safety rules for cross-Region failover, and zonal shift / zonal autoshift for AZ-impairment recovery. Applies when setting up failover routing, configuring safety rules, enabling zonal shift, or configuring zonal autoshift with practice runs. Also applies when shifting traffic out of a specific Availability Zone (AZ) for an ALB/NLB or other resource. For a broader "an AZ is impaired, what is my response across services" question, see aws-resilience-lifecycle. Does not apply to Resilience Hub setup or FIS experiments.
Frontend & fullstack development with live preview. Use when the user wants to build a web page, frontend app, fullstack project, or any web UI — including React, Vue, Vite, static HTML, Express, FastAPI, or any framework that produces a browser-viewable result. Also use when the user wants to deploy, publish, or share a preview to the public internet (community publish).
Answer questions about LLM and agentic-application behavior from data already ingested into Elastic: latency and error rate, token and cost utilization, response quality and guardrail events, and agentic call-chain orchestration. Use when the user asks about LLM monitoring, GenAI observability, token spend or AI cost, model latency, prompt or guardrail failures, or how an agent's tool-call chain executed.
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.
Review the current Kelos branch, or an explicitly specified PR, issue, or diff, for Kubernetes API and CRD design quality. Use when asked for a Kelos API review, CRD/API compatibility review, Kubernetes API convention review, or review of changes under api/, generated CRDs, examples/, or self-development/ manifests. Default to the current branch when no target is specified. This skill is review-only.
Search and read official Coralogix platform documentation using **`cx docs search`** and **`cx docs fetch`**. Use when the user asks how Coralogix features work, how to configure or use the UI, set up integrations (OpenTelemetry, agents, collectors, webhooks), manage API keys, explore spans/traces/logs in the product, configure alerts/SLOs/dashboards, or needs authoritative product docs — not live tenant telemetry.
Creates a complete EC2 Image Builder pipeline that builds a custom AMI with pre-installed software, distributes it to target regions, executes the pipeline, and creates a launch template. Use when setting up automated AMI creation with IAM roles, build components, image recipes, and infrastructure configuration.
Expert evaluator for Prometheus label strategy on Grafana Cloud. Audits, designs, and improves label schemas using cardinality scoring, access-pattern alignment, static vs. dynamic label rules, histogram bucket discipline, and instrumentation hygiene. Prevents high cardinality at the source — in application code and scrape target labels — without dropping labels that make series unique (which breaks the data). For reducing the cost of series already in Grafana Cloud, routes to the adaptive-metrics skill. Use when the user asks to evaluate, audit, design, or improve Prometheus labels — or asks how to prevent high cardinality at the source. For "why is my Prometheus slow / expensive right now" triage, see prometheus-cardinality-troubleshooter.
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.