Skill-uri pentru agenți pe care le poți verifica înainte să le instalezi
Skill-uri SKILL.md publice din depozite GitHub cu peste 50 de stele și de la producători, scanate și evaluate. Instalează oricare dintre ele cu o singură comandă în Claude Code, Cursor, Codex, GitHub Copilot sau Gemini CLI.
8.895 de skill-uri din 259 de depozite · actualizat acum 32 de minute
603 skill-uri
- terraform-skillantonbabenko/terraform-skillUse when writing, reviewing, or debugging Terraform/OpenTofu modules, tests, CI, scans, or state ops - diagnoses failure mode (identity churn, secrets, blast radius, CI drift, state corruption) with version-aware guards.DevOpsFără avertismente★ 2,4 K↓ —
- boltz2-nimNVIDIA/skillsUse Boltz2 NIM for biomolecular structure prediction and binding affinity. Invoke for Boltz2, protein structures, protein-ligand/DNA/RNA complexes, SMILES or CCD ligands, pIC50/IC50 affinity scoring, mmCIF output, hosted NVIDIA API calls, or local Docker deployment.DevOpsFără avertismente★ 3,7 K↓ —
- doca-setupNVIDIA/skillsUse this skill when the user is dealing with the DOCA environment around their workload — verifying an install is healthy, preparing the build env (pkg-config, headers, LD_LIBRARY_PATH, hugepages, devlink, representors), debugging env-class failures, deciding container-vs-bare-metal deployment shape, or reaching a DOCA install from a host that doesn't have one yet via the NGC DOCA container Stage-1 fallback. Trigger even when the user does not explicitly mention "DOCA setup" — typical implicit phrasings include "just got a BlueField, what now", "code is built, how to run it", "pkg-config can't find doca-flow", "no free 2048 kB hugepages", "representor X not found", "on a Mac and want to learn DOCA". Refuse and route elsewhere for library API specifics (Flow pipes, RDMA queues), the modify-a-sample first-app workflow or DOCA_ERROR_* program-side debugging, and "where is X documented" knowledge-map questions — those belong to other skills.DevOpsFără avertismente★ 3,7 K↓ —
- latchbio-integrationforyourhealth111-pixel/Vibe-SkillsLatch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.DevOpsFără avertismente★ 3,7 K↓ —
- tao-run-on-virtualenvNVIDIA/skillsRun a Python training/eval script directly in an existing local virtualenv — no docker, no container. Implements the four-verb consumer contract (submit/status/logs/cancel) over a vendored process-lifecycle runner with durable on-disk state, PID-reuse-safe identity, and process-group cleanup. Use for docker-free local execution, plain-Python model scripts, fast HPO/AutoML trial smokes, or hosts where containers are unavailable. Trigger phrases include "run in my venv", "no docker", "virtualenv execution", "local python training", "run this training script directly".DevOpsFără avertismente★ 3,7 K↓ —
- sarif-parsingtrailofbits/skillsParses and processes SARIF files from static analysis tools like CodeQL, Semgrep, or other scanners. Triggers on "parse sarif", "read scan results", "aggregate findings", "deduplicate alerts", or "process sarif output". Handles filtering, deduplication, format conversion, and CI/CD integration of SARIF data. Does NOT run scans — use the Semgrep or CodeQL skills for that.DevOpsFără avertismente★ 7,7 K↓ —
- senior-ml-engineerforyourhealth111-pixel/Vibe-SkillsWorld-class ML engineering skill for productionizing ML models, MLOps, and building scalable ML systems. Expertise in PyTorch, TensorFlow, model deployment, feature stores, model monitoring, and ML infrastructure. Includes LLM integration, fine-tuning, RAG systems, and agentic AI. Use when deploying ML models, building ML platforms, implementing MLOps, or integrating LLMs into production systems.DevOpsFără avertismente★ 3,7 K↓ —
- senior-computer-visionforyourhealth111-pixel/Vibe-SkillsWorld-class computer vision skill for image/video processing, object detection, segmentation, and visual AI systems. Expertise in PyTorch, OpenCV, YOLO, SAM, diffusion models, and vision transformers. Includes 3D vision, video analysis, real-time processing, and production deployment. Use when building vision AI systems, implementing object detection, training custom vision models, or optimizing inference pipelines.DevOpsFără avertismente★ 3,7 K↓ —
- warp-evalNVIDIA/skillsEvaluate whether an existing hot path is a credible NVIDIA Warp candidate. Use for irregular or spatial queries, particle or geometry simulation, branch-heavy loops, many small launches, host fallbacks, or large intermediates. CPU-only code and absent GPU dependencies are normal unless NVIDIA is prohibited. Exclude required cross-vendor or CPU-only deployment, vendor-lowered dense or NN layers, general Warp API questions, and already-selected Warp kernels. Contribution policy alone is not exclusion.DevOpsFără avertismente★ 3,7 K↓ —
- tao-data-ioNVIDIA/skillsThe data-mover for TAO jobs — decides the storage tier (A pre-positioned mount with zero fetch / B volume-from-S3 / C ephemeral in-compute fetch), stages inputs (bulk + annotation-selective + archive extract + HF/NGC PTM), maps credentials to env, routes outputs 3-way with upload-excludes, and runs the compute-frame verify gate. A support skill other platform skills (docker, kubernetes, slurm, brev, virtualenv) call to get data to and from the compute container without the TAO SDK. Trigger phrases include "stage inputs", "mount the dataset", "upload TAO results", "download only referenced files", "resolve results_dir", "verify the container can read the data".DevOpsFără avertismente★ 3,7 K↓ —
- nvflare-autoflNVIDIA/skillsUse for agent-assisted Auto-FL optimization of an existing NVFLARE job in simulation, POC, or production. Do not use for code conversion, diagnosis-only work, or deployment setup.DevOpsFără avertismente★ 3,7 K↓ —
- tao-run-automlNVIDIA/skillsRun container-backed AutoML / hyperparameter optimization (HPO) for NVIDIA TAO networks using AutoMLRunner. Handles algorithm selection (bayesian, hyperband, asha, bohb, llm, hybrid, autoresearch), WandB experiment tracking, job execution on any TAO SDK platform, result interpretation, and per-rec custom evaluation hooks. Use when the user mentions TAO AutoML, hyperparameter optimization, HPO, automl, automl_settings, AutoMLRunner, tao_automl, bayesian search, hyperband, ASHA, LLM-guided search, autoresearch, or wants to tune train/evaluate/inference/distill/prune/quantize for a TAO network. Model actions use the resolved image; venv training requires an explicit request. Platform-agnostic — runs on any SDK (Brev, SLURM, Kubernetes, Docker). Do not use generic "keep improving" language alone to override a matching domain-specific DEFT workflow; attribute-labelled CLIP / SigLIP image-retrieval loops belong to tao-run-deft-pas unless HPO is explicit.DevOpsFără avertismente★ 3,7 K↓ —
- nvshmem-installNVIDIA/skillsPlan and validate NVSHMEM and NVSHMEM4Py installations. Use for package, container, or source deployments.DevOpsFără avertismente★ 3,7 K↓ —
- nvflare-fed-statsNVIDIA/skillsCompute federated statistics over tabular data (count, sum, mean, stddev, var, histogram, quantile, noise-protected min/max) and image data (count, failure_count, pixel-intensity histogram) across NVFLARE sites via FedStatsRecipe — automatic and non-interactive from the dataset, feature names (header or supplied), and optionally a README or notes declaring which statistics to compute; do not use for model training conversion, hierarchical statistics, deployment, POC/production lifecycle, or failed-job diagnosis.DevOpsFără avertismente★ 3,7 K↓ —
- vss-build-vision-aiNVIDIA/skillsAdd agent-ready vision capabilities — dense captioning, detection, search, alerting, summarization — to an agent or application through a customizable, self-contained vision stack built on the NVIDIA VSS Blueprint. Use this skill when a developer or agent wants to give their app vision: pick capabilities via guided intake ("build a vision agent", "add vision capabilities") or describe them in natural language ("create a profile for streaming dense captioning", "add agentic search to my base deployment", "deploy warehouse 3d"). Route, compose, configure, and deploy stock base, alerts, LVS, search developer profiles, or the warehouse industry profile and lean custom combinations expressed as delta overlays using one current developer profile as the Foundation. Not for operating a stack that is already deployed — searching, asking about a video, summarizing, managing alerts, or generating a report — and not for deploying a single microservice on its own; use the matching vss-* skill for those.DevOpsFără avertismente★ 3,7 K↓ —
- nemotron-asr-finetuneNVIDIA/skillsOrchestration skill for NVIDIA Nemotron Speech (Riva) / NeMo ASR domain and language adaptation. Given a goal like "improve/fine-tune ASR for my domain or language", it scopes the task, picks the cheapest sufficient path (word boosting → n-gram LM → fine-tuning), delegates each stage to the right sub-skill (data generation, training, evaluation, deployment), and answers cost/time/data questions along the way.DevOpsFără avertismente★ 3,7 K↓ —
- tao-run-on-kubernetesNVIDIA/skillsKubernetes execution platform — submits TAO container jobs as k8s Jobs with NVIDIA GPU scheduling; single-pod for one node, Indexed Jobs for multi-node distributed training. Use when running on EKS / GKE / AKS / on-prem clusters with the NVIDIA GPU Operator installed, or when integrating TAO into an existing k8s-native ML platform.DevOpsFără avertismente★ 3,7 K↓ —
- nvflare-convert-pytorchNVIDIA/skillsConvert existing plain or manual PyTorch training code into an NVFLARE federated job using Client API model exchange, local validation, and job export; use when the user names plain PyTorch or preliminary source inspection identifies one plain-PyTorch owner, and not for Lightning, other frameworks, deployment, POC/production lifecycle, or experiment workflows.DevOpsFără avertismente★ 3,7 K↓ —
- nvflare-convert-lightningNVIDIA/skillsConvert existing PyTorch Lightning training code into an NVFLARE federated job using the Lightning Client API patch, local validation, and job export; use only when the request names federated/NVFLARE conversion or asks multiple sites to train collaboratively while keeping each site's data local, and either names PyTorch Lightning or preliminary source inspection identifies one Lightning owner; do not use for non-federated Lightning work such as DDP, profiling, inference serving, or training-loop changes, nor for plain PyTorch, TensorFlow/Keras, other frameworks, deployment, POC/production lifecycle, or experiment workflows.DevOpsFără avertismente★ 3,7 K↓ —
- omniverse-cad-to-simreadyNVIDIA/skillsCoordinate the end-to-end CAD/source-asset to SimReady workflow. Use for broad requests such as CAD to SimReady, source asset to simulation-ready USD, or prop packaging that require conversion, material/physics assignment, SimReady conformance, validation, and optional package creation; deploy or verify Content Agents services first when property assignment is enabled; route single-stage work through nested references.DevOpsFără avertismente★ 3,7 K↓ —
- tao-setup-nvidia-gpu-hostNVIDIA/skillsHost setup for TAO GPU backends. Checks and, after user approval, installs minimum-compatible NVIDIA driver, CUDA Toolkit, and NVIDIA Container Toolkit versions for Docker/local-Docker and Kubernetes GPU worker hosts. TAO-wide defaults can be overridden by the selected model's runtime profile. The `--check-only` path works on any Linux distribution; `--install` automates debian-family (Ubuntu/Debian/Pop!_OS/Mint/Zorin/Raspbian), rhel-family (Fedora/RHEL/Rocky/AlmaLinux), and suse-family (openSUSE/SLES) hosts, and prints actionable manual-install steps for everything else. Use when the user asks to "set up an NVIDIA GPU host", "check TAO Docker GPU runtime", or prepare a Kubernetes GPU worker for TAO.DevOpsFără avertismente★ 3,7 K↓ —
- offensive-dependency-confusionSnailSploit/Claude-RedDeep-dive offensive methodology for dependency confusion and namespace attacks across all major package ecosystems. Covers npm scope confusion exploiting the gap between public and private scoped packages and .npmrc misconfigurations where registry mappings fail to pin internal scopes exclusively. Addresses PyPI namespace attacks through --extra-index-url resolution ordering, NuGet feed priority exploitation when multiple package sources are configured without clear directives, Maven and Gradle repository ordering where artifact resolution traverses repositories sequentially, Go module proxy abuse through GOPROXY misconfiguration, Ruby gems namespace squatting, and Docker image tag confusion with unqualified image references. Provides complete proof-of-concept methodology using safe callbacks including DNS canary via interactsh or Burp Collaborator and HTTP beacon with no destructive payload. Covers reconnaissance techniques for discovering internal package names through GitHub repository analysis, error messDevOpsVerifică întâi★ 7,7 K↓ —
- pnp-markets-solanainternet-court/internet-court-skillCreate, trade, and settle permissionless prediction markets on Solana. Use when building prediction market infrastructure, creating social media markets (Twitter/YouTube/DeFiLlama), setting up custom oracle resolution, P2P betting, or autonomous agent-driven forecasting. Supports V2 AMM, P2P (V3), and custom oracle markets with any SPL token collateral (including Token-2022).DevOpsFără avertismente★ 6,8 K↓ —
- kubesphere-devops-pipelinekubesphere/kubesphereUse when creating, running, or managing CI/CD pipelines in KubeSphere DevOps, including pipeline API operations and run monitoringDevOpsFără avertismente★ 17,1 K↓ —
kubesphere-devops-pipeline
kubesphere/kubesphere
DevOpsActualizat 15 iul. 2026
De la autor
Use when creating, running, or managing CI/CD pipelines in KubeSphere DevOps, including pipeline API operations and run monitoring
Instalare
npx skills add kubesphere/kubesphere --skill kubesphere-devops-pipeline -a claude-code
Se instalează în .claude/skills/kubesphere-devops-pipeline/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Fără descărcare: licența acestui skill (Personalizată sau neclară) nu ne permite să-i redistribuim fișierele. Comenzile de instalare le iau direct de pe GitHub.
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