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AI & LLM Engineering · Python · For devops and sre engineers
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Skills
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| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Give the human an off switch and a cost meter for the coding agents on this machine, using ClawMetry. | vivekchand/ | 425 | — | ~1.1k | Automated safety check: Pass | MIT | today |
| 2 | Diagnose and fix Cosmos3 environment, installation, and runtime errors. | NVIDIA/ | 558 | — | ~1.3k | Automated safety check: Notes | Unknown | today |
| 3 | Builds a NeMo Gym (NVIDIA) variant of an RL environment. An agent skill from adithya-s-k/FineEnvs. | adithya-s-k/ | 443 | — | ~2.1k | Automated safety check: Pass | Apache-2.0 | yesterday |
| 4 | Read your own agent telemetry from ClawMetry (waste, progress, cost) and act on it before finishing a task. | vivekchand/ | 425 | — | ~515 | Automated safety check: Pass | MIT | today |
| 5 | 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 | yesterday |
| 6 | Deploys LLMs with vLLM for high-throughput serving, covering the OpenAI-compatible server, offline batch inference, monitoring and a Docker rollout. | Orchestra-Research/ | 13k | 6 repos | ~2.3k | Automated safety check: Pass | MIT | 3 mo ago |
| 7 | Optimizes and serves LLMs on NVIDIA GPUs with TensorRT-LLM, covering quantization, in-flight batching, multi-GPU parallelism and the trtllm-serve command. | Orchestra-Research/ | 13k | 5 repos | ~1.3k | Automated safety check: Pass | MIT | 3 mo ago |
| 8 | Naming conventions for SGLang speculative decoding identifiers. | sgl-project/ | 37k | 2 repos | ~1.6k | Automated safety check: Pass | Apache-2.0 | today |
| 9 | Diagnose, troubleshoot, and advise on any Qdrant deployment by loading the latest official Qdrant skills live from skills.qdrant.tech. | qdrant/ | 253 | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | yesterday |
| 10 | Builds an Open Reward Standard (ORS) variant of an RL environment using the official openreward Python package. | adithya-s-k/ | 443 | — | ~2.3k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 11 | Bootstrap a reproducible LLM Observability experiment through the Python ddtrace SDK or the Node dd-trace SDK. | datadog-labs/ | 177 | — | ~2.3k | Automated safety check: Pass | MIT | today |
| 12 | 12.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 | yesterday |
| 13 | 13.Verify Verify a Txtify change end-to-end. An agent skill from lkmeta/txtify. | lkmeta/ | 135 | — | ~583 | Automated safety check: Pass | Apache-2.0 | 1 mo ago |
| 14 | Shows how to launch distributed Megatron-LM training on a SLURM cluster: sbatch skeleton, torch.distributed.run setup, CUDA_DEVICE_MAX_CONNECTIONS rules and failure diagnosis. | NVIDIA/ | 18k | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | today |
| 15 | Azure AI Content Safety SDK for Python. An agent skill from microsoft/skills. | microsoft/ | 3.1k | 6 repos | ~2.2k | Automated safety check: Pass | MIT | yesterday |
| 16 | Expert guidance on the Google Agent Development Kit (ADK) for Python. | cnemri/ | 127 | — | ~769 | Automated safety check: Pass | MIT | 8 mo ago |
| 17 | OCI Data Science service patterns including Jobs, Pipelines, Model Catalog, authentication, and the ADS SDK beyond AQUA. | oracle/ | 125 | — | ~2.1k | Automated safety check: Pass | UPL-1.0 | 1 mo ago |
| 18 | Configures Hyperloom after pip install --target . An agent skill from AMD-AGI/Hyperloom. | AMD-AGI/ | 217 | — | ~7.2k | Automated safety check: Notes | Unknown | today |
| 19 | Apply Karpathy-style minimalism and anti-dependency principles to code and system design. | LearnPrompt/ | 109 | — | ~1.6k | Automated safety check: Pass | MIT | 2 mo ago |
| 20 | Bootstrap evaluators from production traces — by default propose online LLM-judge evaluators and, after you confirm, create them in Datadog as disabled drafts (never auto-enabled); on request emit… | datadog-labs/ | 177 | — | ~25k | Automated safety check: Pass | MIT | today |
| 21 | 21.Ultralytics A skill your agent uses for Ultralytics YOLO package workflows: CLI/Python model usage, data/config setup, train/val, prediction/results, export/deployment, tracking/solutions, model-family… | VectorSpaceLab/ | 328 | — | ~1.2k | Automated safety check: Pass | AGPL-3.0 | 1 mo ago |