Marketplace
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.
- 143.8K
- listings
- 1
- installs
- 0
- reviews
- 38.7K
- publishers
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.
coreweave-hello-world
Deploy a GPU workload on CoreWeave with kubectl. Use when running your first GPU job, testing inference, or verifying CoreWeave cluster access. Trigger with phrases like "coreweave hello world", "core
coreweave-incident-runbook
Incident response runbook for CoreWeave GPU workload failures. Use when inference services are down, GPUs are unavailable, or responding to production incidents on CoreWeave. Trigger with phrases like
coreweave-install-auth
Configure CoreWeave Kubernetes Service (CKS) access with kubeconfig and API tokens. Use when setting up kubectl access to CoreWeave, configuring CKS clusters, or authenticating with CoreWeave cloud se
coreweave-local-dev-loop
Set up local development workflow for CoreWeave GPU deployments. Use when building containers locally, testing YAML manifests, or iterating on model serving configurations before deploying. Trigger wi
coreweave-multi-env-setup
Configure CoreWeave across development, staging, and production environments. Use when setting up multi-environment GPU infrastructure, separating namespaces, or managing per-environment GPU quotas. T
coreweave-observability
Set up GPU monitoring and observability for CoreWeave workloads. Use when implementing GPU metrics dashboards, configuring alerts, or tracking inference latency and throughput. Trigger with phrases li
coreweave-performance-tuning
Optimize CoreWeave GPU inference latency and throughput. Use when reducing inference latency, maximizing GPU utilization, or tuning batch sizes and concurrency. Trigger with phrases like "coreweave pe
coreweave-prod-checklist
Production readiness checklist for CoreWeave GPU workloads. Use when launching inference services, preparing GPU training for production, or validating deployment configurations. Trigger with phrases
coreweave-sdk-patterns
Production-ready patterns for CoreWeave GPU workload management with kubectl and Python. Use when building inference clients, managing GPU deployments programmatically, or creating reusable CoreWeave
coreweave-security-basics
Secure CoreWeave deployments with RBAC, network policies, and secrets management. Use when hardening GPU workloads, managing model access, or configuring namespace isolation. Trigger with phrases like
coreweave-upgrade-migration
Upgrade CoreWeave deployments and migrate between GPU types. Use when migrating from A100 to H100, upgrading CUDA versions, or updating inference server versions. Trigger with phrases like "upgrade co
together-common-errors
Together AI common errors for inference, fine-tuning, and model deployment. Use when working with Together AI's OpenAI-compatible API. Trigger: "together common errors".
together-core-workflow-b
Together AI core workflow b for inference, fine-tuning, and model deployment. Use when working with Together AI's OpenAI-compatible API. Trigger: "together core workflow b".
together-install-auth
Install Together AI SDK and configure API key for inference and fine-tuning. Use when setting up Together AI, configuring the OpenAI-compatible API, or initializing the together Python package. Trigge
together-prod-checklist
Together AI prod checklist for inference, fine-tuning, and model deployment. Use when working with Together AI's OpenAI-compatible API. Trigger: "together prod checklist".
pi-inngest
Use Pi from Inngest safely in joelclaw. Covers event-driven detached Pi CLI runners, direct pi-ai calls inside step.run, service-account OAuth auth, claim-check files, and when to choose each pattern.
lambda-labs-gpu-cloud
Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clust
hqq-quantization
Half-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast quantization workflows, or when deployin
earth2studio-deterministic-forecast
Build deterministic forecast scripts with Earth2Studio (model, data source, IO, inference). Do NOT use for ensemble, diagnostics, data-only fetch, or install.
jetson-inference-mem-tune
Pick the serving stack and per-runtime memory flags (vLLM, SGLang, llama.cpp, TensorRT Edge-LLM) for an LLM/VLM workload on any NVIDIA Jetson.
tao-run-inference-service
Start, query, and stop a network-specific TAO inference microservice ({network_arch}-inference-microservice) by delegating container execution to the appropriate platform skill. Handles container imag
lambda-labs-gpu-cloud
Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clust
hqq-quantization
Half-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast quantization workflows, or when deployin
harness-venice
Fund Venice AI inference (venice.ai) with staked DIEM on Base. Buy DIEM, stake it on the DIEM token contract for a daily API allowance, and mint an agent-owned INFERENCE key via Venice's web3 key endp
Find
Search or browse by kind. Every card shows who made it, how many people installed it and what they think.
Install
One click. You get a manifest the router understands, plus copy-paste snippets for the CLI, Python and YAML.
Rate and publish
Leave a star rating after you have used it. Made something useful? Publish it - free listings go live immediately.
Prefer the terminal? osr stack apply registry://starter installs the starter template.