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Everything your AI needs, in one place.
Ready-made agents, skills, personas, prompts, templates and tools. Each one is checked before it goes live, works with any model, and installs in a click. Rate what you use so the best rises to the top.
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A service that does a whole job for you - research, coding, support - and reports back.
Step-by-step instructions an AI follows for one kind of task. Install once, reuse everywhere.
A voice and set of rules layered onto any model: tone, audience, do's and don'ts.
A ready-to-use prompt with fill-in-the-blank variables and notes on when it works best.
A complete routing setup - models, rules and settings - in one file you can apply in a minute.
A single function an AI can call: a calculator, a search, a database lookup.
A language model endpoint with its price, speed and quality declared so the router can compare it.
docker-auto-deploy
Deploy Docker web apps with cron-triggered git auto-update, zero-downtime restarts, and 502 troubleshooting. Covers the git-poll + docker-compose rebuild pattern for self-hosted apps.
optimize-docker-build-cache
Optimize Docker build times using layer caching, multi-stage builds, BuildKit features, and dependency-first copy patterns. Applicable to R, Node.js, and Python projects. Use when Docker builds are sl
create-multistage-dockerfile
Create multi-stage Dockerfiles that separate build and runtime environments for minimal production images. Covers builder/runtime stage separation, artifact copying, scratch/distroless/alpine targets,
langchain-deploy-integration
Deploy LangChain applications to production with LangServe, Docker, and cloud platforms (Cloud Run, AWS Lambda). Trigger: "deploy langchain", "langchain production deploy", "langchain docker", "langch
implementing-container-image-minimal-base-with-distroless
Reduce container attack surface by building application images on Google distroless base images that contain only the application runtime with no shell, package manager, or unnecessary OS utilities.
hardening-docker-containers-for-production
Hardening Docker containers for production involves applying security best practices aligned with CIS Docker Benchmark v1.8.0 to minimize attack surface, prevent privilege escalation, and enforce leas
docker-compose
Docker Compose patterns for development and production environments. Use this skill when writing or maintaining Docker Compose configurations, Dockerfiles, or containerized development workflows. Cove
hardening-docker-daemon-configuration
Harden the Docker daemon (dockerd) by configuring /etc/docker/daemon.json with user namespace remapping, TLS client authentication, seccomp profiles, and CIS Docker Benchmark controls such as icc, no-
deep-diagnosis-optimization
Systematic codebase diagnosis → prioritized batch optimization → kimi+container triple verification → CI green → merge to main. A proven end-to-end workflow for deeply auditing a codebase, fixing issu
DevOps & Deployment
Use when setting up CI/CD pipelines, containerizing applications, deploying to Kubernetes, or writing infrastructure as code. DevOps & Deployment covers GitHub Actions, Docker, Helm, and Terraform pat
supabase-local-dev-loop
Configure Supabase local development with the CLI, Docker, and migration workflow. Use when initializing a Supabase project locally, starting the local stack, writing migrations, seeding data, or iter
model-deployment
Deploy ML models with FastAPI, Docker, Kubernetes. Use for serving predictions, containerization, monitoring, drift detection, or encountering latency issues, health check failures, version conflicts.
nemo-evaluator-sdk
Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. Use when needing scalable evaluation on local Docker, Slurm HPC, or cloud p
nemo-evaluator-sdk
Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. Use when needing scalable evaluation on local Docker, Slurm HPC, or cloud p
tdsk-cli
Knowledge base for the developer CLI repo - DevOps orchestration for Docker, Kubernetes, and DevSpace
deployment-automation
Automate application deployment to cloud platforms and servers. Use when setting up CI/CD pipelines, deploying to Docker/Kubernetes, or configuring cloud infrastructure. Handles GitHub Actions, Docker
analyzing-docker-container-forensics
Investigate compromised Docker containers by analyzing images, layers, volumes, logs, and runtime artifacts to identify malicious activity and evidence.
setup-local-kubernetes
Set up a local Kubernetes development environment using kind, k3d, or minikube for fast inner-loop development. Covers cluster creation, ingress configuration, local registry setup, and integration wi
golang-testing
Write idiomatic Go tests — unit tests, table-driven patterns, mocking, and testcontainers-go integration tests against real Postgres, Redis, and other containerised dependencies.
testcontainers-go
Use this skill when writing Go integration tests with Docker containers, using testcontainers-go modules (postgres, redis, kafka, etc.), setting up container-based test infrastructure, or configuring
esios-nan-deploy
Procedimiento de deploy de proyectos Node.js en NaN.builders — Dockerfile, Kaniko, variables de entorno, puertos y troubleshooting.
docker-kubernetes
Use when writing production Dockerfiles, configuring docker-compose, authoring Kubernetes manifests or Helm charts, hardening container security, or designing ingress and service mesh topologies. Hand
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Install
One click. You get a manifest the router understands, plus copy-paste snippets for the CLI, Python and YAML.
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Prefer the terminal? osr stack apply registry://starter installs the starter template.