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.
46.700 de skill-uri din 2.243 de depozite · actualizat acum 20 de ore
45.646 de skill-uri
- auth-patternsdavepoon/buildwithclaudeThis skill should be used when the user asks about "authentication in Next.js", "NextAuth", "Auth.js", "middleware auth", "protected routes", "session management", "JWT", "login flow", or needs guidance on implementing authentication and authorization in Next.js applications.AlteleFără avertismente★ 3,7 K↓ —
- tao-run-inference-serviceNVIDIA/skillsStart, query, and stop a network-specific TAO inference microservice ({network_arch}-inference-microservice) by delegating container execution to the appropriate platform skill. Handles container image resolution, job-payload JSON construction, and the service registry. Use when the user wants to run inference on a TAO model checkpoint using a microservice container, deploy a TAO inference endpoint, or stop a running inference container.DevOpsFără avertismente★ 3,8 K↓ —
- ctf-ai-mlljagiello/ctf-skillsProvides AI and machine learning techniques for CTF challenges. Use when attacking ML models, crafting adversarial examples, performing model extraction, prompt injection, membership inference, training data poisoning, fine-tuning manipulation, neural network analysis, LoRA adapter exploitation, LLM jailbreaking, or solving AI-related puzzles.AlteleFără avertismente★ 3,5 K↓ —
- nemo-fabric-build-adapterNVIDIA/skillsBuild, migrate, review, and maintain third-party NVIDIA NeMo Fabric adapters against the public adapter contract. Use when creating adapter or target descriptors, mapping AgentConfig into an agent harness or custom-agent runtime, implementing start/invoke/stop, declaring schemas and capabilities, packaging discovery metadata, or assessing adapter conformance. Do not use for consumer applications that only call the NVIDIA NeMo Fabric SDK.JuridicFără avertismente★ 3,8 K↓ —
- tao-finetune-kumo-anomalyNVIDIA/skillsKumo-Anomaly — diffusion-based anomaly detection and fine-tuning for multivariate time series. Use when the user asks to "fine-tune Kumo-Anomaly", "run Kumo-Anomaly inference", "detect anomalies with diffusion", "time series anomaly detection", "finetune Kumo-Anomaly", "use perform_anomaly_analysis_with_diffusion", "automl Kumo-Anomaly", "hyperparameter search Kumo-Anomaly", "hyperparameter optimization" or mentions "curriculum_medium.yaml", "final_model.pth", "kumo-anomaly", "sdk/anomaly_analysis", or "TSDiffuser_Generic".AlteleFără avertismente★ 3,8 K↓ —
- exploits-searchdavepoon/buildwithclaudeSearch for exploits across all vulnerabilities with filtering by ecosystem, severity, source, and EPSSSecuritateFără avertismente★ 3,7 K↓ —
- nemotron-retrieval-recipesNVIDIA/skillsUse when planning, debugging, tuning, evaluating, exporting, or deploying public Nemotron `embed`/`rerank` retrieval recipes.DevOpsFără avertismente★ 3,8 K↓ —
- holoscan-install-condaNVIDIA/skillsHandle Holoscan SDK 5.x Conda installation requests: explain 5.0 package unavailability, check later releases, and select a supported installation method.AlteleFără avertismente★ 3,8 K↓ —
- tao-generate-anomaliesNVIDIA/skillsFull PAIDF AnomalyGen pipeline — fine-tune on a new anomaly dataset, generate synthetic anomaly images (SDG), evaluate quality (nn_score), and search per-sample (guidance, crop_ratio) parameters. Three modes: full (Phase 0→7: finetune then generate), finetune_only (Phase 0→1: train only), inference_only (Phase 0, 2→7: generate from an existing checkpoint). Use when the user asks to "fine-tune AnomalyGen", "generate anomaly images", "run PAIDF SDG", "evaluate SDG output quality", "run per-sample search", or run any part of the AnomalyGen pipeline, even if they only mention one phase.AlteleFără avertismente★ 3,8 K↓ —
- tao-run-dinov3-ssl-deftNVIDIA/skillsRun iterative DINOv3 SSL DEFT data selection and retraining from an unlabeled pool, using GRIT or multi-task weakness and fixed-encoder retrieval. Use for active-learning-style DINOv3 mining, not plain pretraining/fine-tuning (tao-train-dinov3) or AOI/PAS DEFT.ProductivitateFără avertismente★ 3,8 K↓ —
- umap-learnforyourhealth111-pixel/Vibe-SkillsUMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.AlteleFără avertismente★ 3,8 K↓ —Apare și în 1 alt depozit
- directions-labNoupaperclipai/paperclipScaffold a directions lab that shows shipped UI (Today) beside 2-3 design directions, with surface tabs, theme and animation toggles and the V1 MVP hover motion, registered in design-proposals Storybook. Use for a directions page or lab, or to explore design directions next to production.DesignFără avertismente★ 107,8 K↓ —
- holoscan-install-sourceNVIDIA/skillsBuild and verify Holoscan SDK 5.x from an explicit source ref with the repository run wrapper; use for Early Access or SDK development.AlteleFără avertismente★ 3,8 K↓ —
- devil-advocatejeremylongshore/tons-of-skills-marketplaceConstructive critic and stress-tester for ideas and proposals. Use when the user needs to challenge assumptions, find weaknesses, anticipate objections, or strengthen an argument. Trigger with "challenge", "critique", "push back", "poke holes", "stress test", "what am I missing", or "play devil's advocate".TestareFără avertismente★ 2,9 K↓ —
- writing-defect-reportskajisho5/ffmpeg-skillEstablish a finding before you publish it, and correct it after — headlines that overstate what actually reproduces at the layer a user sees, reporting code that no entry point can reach or that is already dead, filing a caveat the project's own records already answered, re-verifying your prior notes against the tree instead of against the note, choosing the narrowest injection point that reproduces a failure without breaking the run first, capturing probe output a harness swallows, and withdrawing a published claim in the thread where you published it. Use when filing an issue, writing the body of a PR or code review that asserts a defect, triaging someone else's report, or deciding whether a suspicious observation is reportable at all.RedactareFără avertismente★ 3,1 K↓ —
- nemo-fabric-integrateNVIDIA/skillsUse this skill when integrating NVIDIA NeMo Fabric into a consumer application, service, evaluation harness, or platform through the typed Python SDK — translating the consumer's own application, job, or deployment config into an in-memory FabricConfig, choosing the single-invocation convenience API or an explicitly started runtime, validating with plan and doctor, and consuming normalized results, artifacts, and telemetry.DevOpsFără avertismente★ 3,8 K↓ —
- rtvi-vlm-customize-modelNVIDIA/skillsHow to swap the VLM in the VSS Alerts Blueprint — covers RTVI-VLM microservice deployment methods, all three VLM consumers (rtvi-vlm, vlm-as-verifier, vss-agent), and health checks.DevOpsFără avertismente★ 3,8 K↓ —
- tiledbvcfforyourhealth111-pixel/Vibe-SkillsEfficient storage and retrieval of genomic variant data using TileDB. Scalable VCF/BCF ingestion, incremental sample addition, compressed storage, parallel queries, and export capabilities for population genomics.ȘtiințăFără avertismente★ 3,8 K↓ —Apare și în 1 alt depozit
- doca-bare-metal-deploymentNVIDIA/skillsRunning a DOCA-linked binary directly on the hardware, with no container or kubelet: on host x86 with a BlueField NIC over PCIe, or bare-metal on BlueField Arm. Use this skill for launching and supervising it (direct, tmux, systemd), and when it "exits 1 right after launch", "systemd keeps restarting it", reports "no matching device on the BF", or the BlueField itself is unhealthy: "bfb-install exited 0 but DPU is dead", "ping 192.168.100.2 works but ssh fails", "host PFs aren't showing netdevs". Refuse service containers under kubelet (doca-container-deployment). Covers PCI/NUMA/CPU/IRQ binding, co-tenant isolation (cgroup-v2/netns/numactl), a seven-layer error taxonomy, platform lifecycle (BFB install, RShim/TMFIFO, host PF rebind, post-BFB recovery) and a six-state BlueField lifecycle classifier. Destructive firmware burn / mlxconfig set requires explicit confirmation via doca-hardware-safety; library APIs, env prep, and build use other skills.DevOpsFără avertismente★ 3,8 K↓ —
- doca-programming-guideNVIDIA/skillsUse this skill when the user is writing their first DOCA app or asking a library-agnostic programming question — picking a shipped sample to copy and modify, wiring pkg-config + meson (or FFI from Rust / Go / Python against the public C ABI), walking the Core lifecycle (create → configure → start → connect → use → stop → destroy), or decoding a DOCA_ERROR_*. Trigger on implicit phrasing: "write my first DOCA program", "meson line for doca_rdma_*", "DOCA_ERROR_BAD_STATE on first call", "call DOCA from Rust", "built clean but nothing on the wire". Refuse install / hugepages / pkg-config (doca-setup), docs or version lookup (doca-public-knowledge-map), and library-internal API work (matching library skill).RedactareFără avertismente★ 3,8 K↓ —
- tao-list-capabilitiesNVIDIA/skillsAnswer what the TAO Skill Bank plugin can do by generating the response from packaged application, data, model, AutoML, and platform manifests. Use when the user asks "what can TAO Skill Bank do", "list TAO models", "which TAO workflows are available", or "what supports AutoML".AlteleFără avertismente★ 3,8 K↓ —
- tao-train-single-stepNVIDIA/skillsStandard single-step train/eval/export workflow for any TAO model. Use when training a TAO model on a dataset without iterative data augmentation, AutoML, or DEFT loops. Trigger phrases include "single train run", "train then evaluate then export", "plain TAO training", "normal training", "no AutoML", "skip the loop". Routes through the per-model SKILL.md for action specifics and through `tao-launch-workflow` for platform/credentials/dataset intake.PlanificareFără avertismente★ 3,8 K↓ —
- card-quoteZJU-REAL/Easel生成适合微博、知乎、公众号或 X/Twitter 分享的 16:9 横版金句卡和数据卡。当用户说“做金句卡、语录卡、数据卡、横版分享卡”时使用。小红书竖版知识卡用 card-xiaohongshu，竖版营销海报用 poster-hero。AlteleFără avertismente★ 4,1 K↓ —
- audio-mixZJU-REAL/Easel音频混合 / 混音：把旁白口播 + 背景音乐 + 音效混成一轨，BGM 自动循环补足并可闪避（旁白说话时自动压低 BGM 保证人声清晰）。当用户说 混音、音频混合、旁白加背景音乐、配音加BGM、人声和音乐混一起、加音效、音频叠加、BGM 压低、闪避、ducking、把配音和bgm合起来 时使用。基于 shared/scripts/audio_mix.py。与 audio-editing concat 区别：concat 是前后顺序拼接，本 SKILL 是同时叠加混音；与 video-editing bgm 区别：那个给视频配乐，本 SKILL 输出纯音频。MediaFără avertismente★ 4,1 K↓ —