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.
48.168 de skill-uri din 2.325 de depozite · actualizat acum 1 oră
48.168 de skill-uri
- fondo-debug-bundlejeremylongshore/tons-of-skills-marketplaceCollect diagnostic information for Fondo support including integration status, transaction discrepancies, and financial data reconciliation issues. Trigger: "fondo debug", "fondo support", "fondo diagnostic", "fondo reconciliation".InginerieFără avertismente★ 2,9 K↓ —
- linear-cost-tuningjeremylongshore/tons-of-skills-marketplaceAnalyze and reduce the infrastructure and quota cost of a Linear integration through workload accounting, query budgets, and push-based updates. Use when a sync is wasteful, throttled, or expensive to operate. Trigger with "reduce Linear API load", "budget Linear queries", or "tune Linear integration cost".DevOpsFără avertismente★ 2,9 K↓ —
- think-harderforyourhealth111-pixel/Vibe-Skills4-phase structured analysis wrapper for vibe pre-routing (compatible with claude-code-settings think-harder semantics).InginerieFără avertismente★ 3,8 K↓ —
- forgetdavepoon/buildwithclaudeDelete a memory from Origin by ID. Destructive and cannot be undone — prefer `/capture` with `supersedes` for corrections. Invoked as `/forget <source_id>`.ProductivitateFără avertismente★ 3,7 K↓ —
- tao-train-bevfusionNVIDIA/skillsBEVFusion for multi-sensor 3D object detection. Fuses LiDAR point clouds and camera images in bird's-eye-view (BEV) space, used in autonomous driving for robust 3D perception. Use when training, evaluating, or running inference for a TAO BEVFusion model. Trigger phrases include "train BEVFusion", "LiDAR + camera fusion", "BEV 3D detection", "multi-sensor 3D perception".AlteleFără avertismente★ 3,8 K↓ —
- linear-hello-worldjeremylongshore/tons-of-skills-marketplaceProve Linear authentication and workspace visibility with the smallest read-only GraphQL or SDK query. Use when establishing a new integration baseline without creating test issues. Trigger with "test Linear connection", "Linear hello world", or "verify Linear API key".TestareFără avertismente★ 2,9 K↓ —
- embedding-strategiesforyourhealth111-pixel/Vibe-SkillsSelect and optimize embedding models for semantic search and RAG applications. Use when choosing embedding models, implementing chunking strategies, or optimizing embedding quality for specific domains.PlanificareFără avertismente★ 3,8 K↓ —
- tao-train-mask-auto-labelNVIDIA/skillsMAL (Mask Auto-Label) for weakly-supervised segmentation. Produces segmentation masks from minimal annotations (point or box annotations) using a ViT-MAE backbone. Use when training, evaluating, or running inference for a TAO MAL model. Trigger phrases include "train MAL", "Mask Auto-Label", "weakly-supervised segmentation", "box-prompted segmentation", "minimal-annotation mask prediction".AlteleFără avertismente★ 3,8 K↓ —
- dialecticforyourhealth111-pixel/Vibe-SkillsMinimal compatibility wrapper for vibe Dialectic Mode (multi-perspective design analysis).DesignFără avertismente★ 3,8 K↓ —
- nemotron-retrieval-recipesNVIDIA/skillsUse when planning, debugging, tuning, evaluating, exporting, or deploying public Nemotron `embed`/`rerank` retrieval recipes.DevOpsFără 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↓ —
- physicsnemo-discoverNVIDIA/skillsOfficial NVIDIA-authored guidance for navigating PhysicsNeMo — pick the model, datapipe, or example for a SciML/AI4Science task (surrogates, forecasting, downscaling, physics-informed, inverse, generative). Points at existing files via live repo search; never writes code. Do NOT use for installation or environment setup, training-loop or other code authoring/scaffolding, contributor/CI/packaging questions, repo-specific questions in physicsnemo-sym/-cfd/-curator, or general (non-physics) ML/PyTorch.ȘtiințăFără avertismente★ 3,8 K↓ —
- codonfm-setupNVIDIA/skillsSet up the public CodonFM v1 repository and download public Encodon checkpoints. Use for requests to build or launch the CodonFM development container, configure local data/checkpoint mounts, verify GPU access, or download public Encodon 80M, 600M, 1B, or Cdwt-1B weights. Do not use for Decodon, Encodon 5B/10B, missense-aggregation, or codon-optimization setup because those implementations are not in the public repository.AlteleFără 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↓ —
- principle-model-the-domainmichael-denyer/pstack-claudeApply when writing stateful logic, or when code branches a lot or repeats a shape assumption across files.RedactareFără avertismente★ 3,7 K↓ —
- data-dashboardplugin87/ux-ui-agent-skillsBuild a dense, data-heavy screen - an analytics console or a trading terminal - with real charts drawn from tokens: candlestick, volume, depth, stacked area, waterfall, scatter, correlation matrix, donut, gauge, sparklines, heatmaps and order books. Use when the request is a dashboard, terminal, monitoring view, data console, or any screen whose job is to show many numbers at once. Covers the layout sequence, the SVG geometry, the accessibility contract per chart type, and the contrast traps that only appear in dark mode.DateFără avertismente★ 3,1 K↓ —
- nemo-retriever-mcpNVIDIA/skillsUse when a task needs to search or add documents through NeMo Retriever MCP.ProductivitateFără avertismente★ 3,8 K↓ —
- mcore-run-on-slurmNVIDIA/skillsHow to launch distributed Megatron-LM training jobs on a SLURM cluster. Covers a minimal sbatch skeleton, environment-variable setup for torch.distributed.run, CUDA_DEVICE_MAX_CONNECTIONS rules across hardware and parallelism modes, container conventions, monitoring, and per-rank failure diagnosis.AlteleFără avertismente★ 3,8 K↓ —
- image-to-codeplugin87/ux-ui-agent-skillsTurn a reference image, screenshot, or mockup into token-driven, accessible code. Infer the design system from the reference (palette, type scale, spacing, radius, layout archetype), map it to the 3-tier tokens, rebuild it, then verify with the kit's gates. Use when the user provides a design/screenshot and wants matching UI code.MediaFără avertismente★ 3,1 K↓ —
- nemo-relay-installNVIDIA/skillsUse this skill when choosing or running NeMo Relay installation for an agent runtime, application language, framework integration, or plugin bundle, or checking a runtime's native Relay readiness. Do not use it for first-run instrumentation or export configuration.AlteleFără avertismente★ 3,8 K↓ —
- tao-train-nvdinov2NVIDIA/skillsNVDINOv2 for self-supervised visual representation learning. Trains vision transformers via self-distillation (teacher-student) without labels and produces general-purpose visual features. Use when training, exporting, or running inference for a TAO NVDINOv2 backbone. Trigger phrases include "train NVDINOv2", "self-supervised ViT pretraining", "DINOv2 backbone", "visual representation learning".AlteleFără avertismente★ 3,8 K↓ —
- hsb-ip-packetizerNVIDIA/skillsChoose or explain HSB Sensor RX packetizer fields for HOLOLINK_def.svh. Do not use for full defs, validation, or runtime APB programming.AlteleFără avertismente★ 3,8 K↓ —
- brandkitplugin87/ux-ui-agent-skillsGenerate a complete, accessible brand design system from a brief, as primitive → semantic → component DTCG tokens (color, type, spacing, radius, shadow, motion), light + dark, plus a single theme.css, verified for WCAG. Use when the user wants a from-scratch brand/design foundation, a new palette + type system, or a themeable token kit for a product.DesignFără avertismente★ 3,1 K↓ —
- mcore-create-issueNVIDIA/skillsInvestigate a failing GitHub Actions run or job and create a GitHub issue for the failure.DevOpsFără avertismente★ 3,8 K↓ —
rag-eval
NVIDIA/skills
AlteleActualizat acum 23 de ore
De la autor
Filesystem RAG benchmarks: corpus/, train.json, evaluate_rag.py (RAGAS quality). Not for prod monitoring, latency/throughput benchmarking (use rag-perf), or evals outside this repo layout.
Instalare
npx skills add NVIDIA/skills --skill rag-eval -a claude-code
Se instalează în .claude/skills/rag-eval/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Descarcă .zip
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
La ce are acces
Doar instrucțiuniNu am văzut acces la rețeaLicență: APACHE-2.0
Verificări de siguranță pe SKILL.md
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De ce 90
Securitate100
Proveniență83
Întreținere100
Licență100
Adopție57
Fișiere (10)
- BENCHMARK.md
- SKILL.md
- eval/h100.json
- eval/nvidia_hosted.json
- references/benchmark-execution.md
- references/dataset-and-conversion.md
- references/evaluate-rag-cli.md
- references/result-analysis.md
- skill-card.md
- skill.oms.sig