Search
AI & LLM Engineering · Kubernetes · For developers
Skills
Sort:BestMost starsTrending todayTrending this weekTrending this monthNewestRecently updatedName
| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Use with the dstack skill for model-serving work when the image, serving command, resources, backend/fleet choice, or service behavior is not proven. | dstackai/ | 2.3k | — | ~1.6k | Automated safety check: Pass | MPL-2.0 | 2 days ago |
| 2 | Create and manage dstack presets: a toolkit that streamlines model inference optimization with agents, and a portable preset format. | dstackai/ | 2.3k | — | ~403 | Automated safety check: Pass | MPL-2.0 | 2 days ago |
| 3 | Use FieldFlow to inspect and reduce noisy JSON CLI output before it reaches model context. | guillaumegay13/ | 110 | — | ~872 | Automated safety check: Pass | MIT | 2 mo ago |
| 4 | Runs OpenAI Codex CLI as a non-interactive worker for CI, Docker, Kubernetes or remote servers, with sandbox modes and JSONL-friendly output. | XiaomiMiMo/ | 14k | — | ~2.7k | Automated safety check: Pass | MIT | 2 days ago |
| 5 | Compose, edit, refactor, and validate Lego-RL train/eval/infer .env configs and reusable scripts/templates modules. | LegoX/ | 113 | — | ~2.1k | Automated safety check: Notes | Apache-2.0 | 3 days ago |
| 6 | 6.Dstack dstack is an open-source control plane for GPU provisioning and orchestration across GPU clouds, Kubernetes, and on-prem clusters. | dstackai/ | 2.3k | — | ~6.2k | Automated safety check: Warn | MPL-2.0 | 2 days ago |
| 7 | Use Langfuse's disposable per-PR previews at pr-N.preview.langfuse.com (synthetic data only). | langfuse/ | 36k | — | ~2.8k | Automated safety check: Notes | Unknown | today |
| 8 | Deploy vLLM to Kubernetes (K8s) with GPU support, health probes, and OpenAI-compatible API endpoint. | vllm-project/ | 102 | — | ~2k | Automated safety check: Pass | Apache-2.0 | 6 mo ago |
| 9 | Deploy and manage vLLM for high-throughput LLM inference. An agent skill from sickn33/agentic-awesome-skills. | sickn33/ | 47k | 2 repos | ~1.7k | Automated safety check: Pass | MIT | 2 days ago |
| 10 | Auto-scale LLM inference clusters on Kubernetes using KEDA, custom GPU metrics, and horizontal pod autoscaling. | sickn33/ | 47k | 1 repo | ~2.1k | Automated safety check: Pass | MIT | 2 days ago |
| 11 | Deploy ML models on Kubernetes with KServe (formerly KFServing) and NVIDIA Triton Inference Server. | sickn33/ | 47k | 1 repo | ~2.3k | Automated safety check: Pass | MIT | 2 days ago |
| 12 | Deploys and optimizes AI/ML inference workloads on GKE, using GPUs, TPUs, and model servers. | google/ | 21k | — | ~2k | Automated safety check: Pass | Apache-2.0 | yesterday |
| 13 | Discovers requirements, and generates architectural, design, and deployment guidance for a retrieval-augmented generation (RAG)-capable enterprise search system in Google Cloud. | google/ | 21k | — | ~4k | Automated safety check: Pass | Apache-2.0 | yesterday |
| 14 | Set up AI Runway on AKS — from bare cluster to running model. | microsoft/ | 255 | 1 repo | ~1.1k | Automated safety check: Pass | MIT | yesterday |
| 15 | Debug live Azure Kubernetes Service (AKS) incidents with a read-only, evidence-first investigation. | microsoft/ | 255 | — | ~3.2k | Automated safety check: Pass | MIT | yesterday |
| 16 | 16.Qzcli Manage GPU compute jobs on the Qizhi (启智) platform using qzcli — a kubectl-style CLI tool. | AI4Scientist/ | 128 | 2 repos | ~1.9k | Automated safety check: Notes | No licence | 4 mo ago |
| 17 | 17.Careful Safety guardrails for destructive commands. An agent skill from mr-daedalium/ostack-saas. | mr-daedalium/ | 114 | 1 repo | ~545 | Automated safety check: Notes | MIT | 6 mo ago |
| 18 | 18.Vllm Operate, configure, benchmark, and troubleshoot vLLM inference servers: Docker and Kubernetes deployment, quantization-aware model configuration (tensor parallelism, KV cache), OpenAI-compatible API… | magnus919/ | 115 | — | ~4.1k | Automated safety check: Notes | MIT | yesterday |
| 19 | Diagnose and fix CoreWeave GPU scheduling, pod, and networking errors. | jeremylongshore/ | 2.8k | — | ~1.1k | Automated safety check: Pass | MIT | yesterday |
| 20 | Deploy a GPU workload on CoreWeave with kubectl. An agent skill from jeremylongshore/tons-of-skills-marketplace. | jeremylongshore/ | 2.8k | — | ~1.4k | Automated safety check: Pass | MIT | yesterday |
| 21 | Auto-scale LLM inference clusters on Kubernetes using KEDA, custom GPU metrics, and horizontal pod autoscaling. | BagelHole/ | 1.2k | — | ~2k | Automated safety check: Pass | MIT | 4 mo ago |
| 22 | Deploy ML models on Kubernetes with KServe (formerly KFServing) and NVIDIA Triton Inference Server. | BagelHole/ | 1.2k | — | ~2.1k | Automated safety check: Pass | MIT | 4 mo ago |
| 23 | Audit, prepare, and deploy PAIDF Orchestration on a Kubernetes GPU cluster - single-GPU H100/L40S hosts, managed Kubernetes, kubeadm, and similar. | NVIDIA/ | 3.6k | — | ~3.8k | Automated safety check: Warn | Apache-2.0 | yesterday |