Skills
The open registry for AI agent skills — structured prompts and workflows with recommended models, example prompts, and compatible tools.
Skills
16
Categories
9
Compatible tools
5
Contributors
1
Showing 1–16 of 16 skills
Produces production-ready nginx configuration for common scenarios: reverse proxy, load balancing, TLS termination, static file serving, HTTP/2, gzip/brotli, caching, rate limiting, and security headers. Explains each directive, warns about risky defaults, and includes a validation step so the config can be tested before reload.
Produces operational runbooks for services and common incidents. Documents prerequisites, step-by-step diagnosis and remediation, exact commands, verification checks, rollback steps, and escalation paths. Structures each runbook so an on-call engineer can follow it under pressure, and keeps destructive steps clearly flagged with safeguards.
Writes idempotent Ansible playbooks and roles from a described target state. Structures tasks with proper handlers, variables, and templates; favors modules over shell commands; applies role-based layout and inventory grouping; and adds check-mode safety and tags. Produces playbooks that are re-runnable without unintended side effects.
Adds production-grade observability to a codebase by instrumenting it with structured logs, metrics, and distributed traces. Recommends span boundaries, cardinality-safe labels, and OpenTelemetry conventions, then generates the wiring code and dashboards needed to make a service debuggable in production.
Writes reusable, well-structured Terraform modules with clean input/output interfaces, sensible defaults, validation rules, and examples. Covers module composition, variable typing and validation, remote state and backends, provider version pinning, and testing with terraform validate/plan and tools like Terratest. Emphasizes least-privilege IAM and safe defaults.
Analyzes cloud spend and produces a FinOps optimization plan. Covers rightsizing, autoscaling, spot/reserved/savings plans, storage tiering, idle resource cleanup, data transfer reduction, and tagging for cost allocation. Prioritizes actions by savings and risk, and defines guardrails and budgets to prevent regressions.
Turns reliability goals into concrete SLIs, SLOs, and error budgets. Helps choose the right service level indicators, set realistic targets from historical data, compute burn rates, and design multi-window multi-burn-rate alerting so teams get paged before the budget is exhausted.
Reviews and rewrites Dockerfiles for smaller images, faster builds, and better security. Applies multi-stage builds, optimal layer ordering and caching, minimal base images, non-root users, and .dockerignore tuning, and flags vulnerabilities and bloat while keeping the build reproducible.
Generates and refactors Helm charts to package Kubernetes applications. Produces templated manifests, values.yaml with sensible defaults, helpers, chart dependencies, and hooks, and parameterizes images, resources, probes, and ingress so a workload can be deployed consistently across environments.
Turns incident timelines, alerts, and chat logs into a clear, blameless postmortem. Produces an executive summary, impact assessment, detailed timeline, root-cause analysis using techniques like the five whys, and a prioritized list of follow-up action items with owners, in a format ready to share with stakeholders.
Designs feature-flagging and progressive-delivery strategies and generates the integration code. Covers flag naming and lifecycle, targeting and segmentation rules, percentage rollouts, kill switches, and cleanup of stale flags across providers like LaunchDarkly, Unleash, Flagsmith, or a homegrown config service.
Generates production-ready Kubernetes manifests — Deployments, Services, Ingresses, ConfigMaps, Secrets, HPAs, and more — from a plain-language description of the workload. Applies best practices for resource limits, health probes, security contexts, and rolling update strategies, with optional Kustomize overlays or Helm chart scaffolding.
Parses and analyzes application, system, and access logs to surface errors, anomalies, and root causes. Correlates events across services, identifies recurring patterns and spikes, extracts structured fields from unstructured lines, and produces a prioritized summary with likely causes and recommended next steps.
Generates and assists with incident response procedures for production systems. Helps with root cause analysis, creates runbooks for common failure modes, builds communication templates for stakeholders, and produces post-incident review documents. Supports SRE and on-call workflows.
Generates Docker Compose configurations from application requirements. Handles service dependencies, networking, volumes, health checks, environment variables, and multi-stage builds. Supports development and production profiles.
Designs and implements CI/CD pipelines for various platforms (GitHub Actions, GitLab CI, Jenkins, CircleCI). Covers build, test, lint, security scan, deploy stages with proper caching, parallelization, and environment management.
Skills vs MCP servers
what's the difference?Skillsthe “what to do”
A skillA reusable, structured prompt/workflow with recommended models, an example prompt, and compatible tools. packages know-how — instructions, an example promptA ready-to-use prompt template that demonstrates how to invoke the skill., and recommended models — so an agent performs a task consistently. Skills add knowledge, not new connections.
MCP serversthe “how to connect”
An MCP serverModel Context Protocol server — a standard way to expose tools, resources, and prompts to AI agents and IDEs. gives an agent new capabilities by connecting it to real systems (databases, APIs, files) over a transportHow the client talks to the server: stdio (local process), SSE, or HTTP streaming.. MCP adds connections and actions, not task instructions.
Rule of thumb: reach for a skill when you need the model to do a task well, and an MCP server when you need it to reach a tool or system. They compose — a skill can rely on tools an MCP server provides.
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