Loading...
Loading...
Found 121 Skills
Specialized Terraform task execution skill for autonomous infrastructure operations. Handles code generation, debugging, version management (1.10-1.14+), security scanning, and architecture design across all providers (AWS 6.0, AzureRM 4.x, GCP) and platforms. Covers ephemeral values, Terraform Stacks, policy-as-code, and 2025 best practices.
Assess and migrate cross-cloud workloads to Azure with migration reports and code conversion guidance. Supports AWS, GCP, and other providers. WHEN: migrate Lambda to Azure Functions, migrate AWS to Azure, Lambda migration assessment, convert AWS serverless to Azure, migration readiness report, migrate from AWS, migrate from GCP, cross-cloud migration.
Configures private network connectivity for CockroachDB Cloud clusters including AWS PrivateLink, GCP Private Service Connect, Azure Private Link, egress private endpoints, and VPC peering. Use when setting up private endpoints to eliminate public internet exposure, configuring egress to external services like Kafka, or establishing VPC peering.
Input template configuration for Elastic integrations. Covers agent stream templates (agent/stream/*.yml.hbs) for all non-CEL input types: HTTPJSON, AWS S3, CloudWatch, Azure Blob, Azure EventHub, GCS, GCP Pub/Sub, TCP, UDP, HTTP Endpoint, Filestream, Logfile, Journald, Winlog, and WebSocket. For CEL input programs, use the cel-programs skill instead.
Design multi-cloud architectures using a decision framework to select and integrate services across AWS, Azure, and GCP. Use when building multi-cloud systems, avoiding vendor lock-in, or leveraging best-of-breed services from multiple providers.
This skill guides writing cloud-init configurations for VM provisioning. Use when creating user_data blocks in Terraform/OpenTofu, or cloud-init YAML for AWS, DigitalOcean, GCP, or Azure instances.
Configure host-based firewalls (iptables, nftables, UFW) and cloud security groups (AWS, GCP, Azure) with practical rules for common scenarios like web servers, databases, and bastion hosts. Use when exposing services, hardening servers, or implementing network segmentation with defense-in-depth strategies.
AWS, GCP, Azure data platforms, infrastructure as code, and cloud-native data solutions
Build modern data apps, dashboards, and interactive reports using either React + Vite or Streamlit. Includes optional Gemini Data Analytics chat integration for an AI powered "chat with your data" experience. Relevant when any of the following conditions are true: 1. User explicitly requests to build a data dashboard, data application, or visualization UI, and the UI pulls data from a GCP database (defaulting to BigQuery unless otherwise specified). 2. You need to generate a frontend web application to interact with, query, and visualize data from GCP data sources. 3. User wants to build a "chat with your data" experience or integrate the Gemini Data Analytics chat API into a web interface. Do NOT use when any of the following conditions are true: 1. The request is for building backend-only services. 2. The request is for simple CLI scripts or command-line applications. 3. The web application is not data-centric or does not involve visualizing/querying data from GCP sources.
Use when assessing cloud infrastructure for security misconfigurations, IAM privilege escalation paths, S3 public exposure, open security group rules, or IaC security gaps. Covers AWS, Azure, and GCP posture assessment with MITRE ATT&CK mapping.
Use when the user asks to set up secret management infrastructure, integrate HashiCorp Vault, configure cloud secret stores (AWS Secrets Manager, Azure Key Vault, GCP Secret Manager), implement secret rotation, or audit secret access patterns.
Guides FinOps analysis on AWS, GCP, and Azure—cost visibility and allocation, tagging and showback/chargeback models, rightsizing and waste removal, RI/Savings Plan/CUD recommendations, budgets and forecasts, anomaly detection, unit economics (cost per service/customer), and FinOps cadence with engineering accountability. Use when optimizing cloud spend, analyzing CUR/billing exports, building cost dashboards, explaining bill spikes, or improving allocation—not for GL mapping, capex, depreciation, or month-end ledger close (compute-accounting-manager), enterprise EA negotiation (enterprise-cloud-architect), hands-on resource provisioning (cloud-engineer), or hardware supply efficiency (data-center-compute-supply-efficiency).