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.
45.604 skill-uri din 2.205 depozite · actualizat acum 22 de ore
45.604 skill-uri
- transformersforyourhealth111-pixel/Vibe-SkillsThis skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.MediaFără avertismente★ 3,8 K↓ —
- skill-algorithm-updatesZJU-REAL/Easel追踪抖音、小红书、B站、微博、知乎和视频号的算法、推荐分发、审核与变现规则变化，并分析对创作者的影响。 当用户说“算法/推荐机制变了吗、流量规则更新、为什么流量下降、平台规则变化”时使用。 内容热点用 skill-trending-topics；泛行业资讯用 skill-news-intelligence；本 SKILL 只看平台机制。AlteleFără avertismente★ 4,1 K↓ —
- brainstormingforyourhealth111-pixel/Vibe-SkillsYou MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.PlanificareFără avertismente★ 3,8 K↓ —Apare și în 1 alt depozit
- skill-cross-platform-diffZJU-REAL/Easel跨平台内容差异深度分析。分析同一话题/内容在不同平台（小红书、抖音、B站、知乎、 微博、公众号、X 等）的呈现差异：内容形式、受众偏好、话语体系、流量逻辑、变现路径。 帮创作者理解"同一个内容在不同平台应该怎么做"。当用户说"小红书和抖音有什么区别"、 "这个话题在B站怎么做"、"跨平台差异"、"不同平台"、"各平台怎么做"、"平台特点"时触发。 和 skill-content-repurposing 的区别：repurposing 做格式适配和内容改写， cross-platform-diff 做深度差异分析和策略洞察。AlteleFără avertismente★ 4,1 K↓ —
- nvidia-appNVIDIA/skillsNVIDIA App MCP: drivers, games, laptops, overlay. Check drivers, manage and optimize games, configure laptop features.AlteleFără avertismente★ 3,7 K↓ —
- i4h-workflow-finetuneNVIDIA/skillsFine-tune a manifest-backed GR00T or openpi remote Task on compatible LeRobot data. Use for training; do not use for inference-only Tasks or checkpoint rollout.ProductivitateFără avertismente★ 3,7 K↓ —
- text-condenserZJU-REAL/Easel字数裁剪/摘要：把长文本压缩到指定字数，保留核心信息。支持硬裁剪（严格字数）、 摘要（保留要点）、金句提取（只保留最精华的句子）三种模式。 特别适合从长文生成平台适配的短文。 使用时机：用户说"裁到 140 字"、"压缩一下"、"太长了"、"摘要"、"精简"、 "缩写"、"字数裁剪"、"帮我缩短"、"提炼要点"。 和 text-polisher 的区别：polisher 润色文案不改长度，condenser 压缩篇幅不做质量提升。AlteleFără avertismente★ 4,1 K↓ —
- principle-make-operations-idempotentmichael-denyer/pstack-claudeApply when designing commands, lifecycle steps, or processing loops that run amid crashes, restarts, and retries. Converge to the same end state regardless of partial prior runs.AlteleFără avertismente★ 3,4 K↓ —
- doca-telemetryNVIDIA/skillsUse this skill to read DOCA hardware-counter events from a `doca_dev` through the per-domain Telemetry reader libraries: `doca_telemetry_pcc`, `_dpa`, `_diag`, `_adp_retx`, `_phy`, and `_pci`. It covers capability checks, context creation, startup, and per-domain reads or samples. Trigger for implicit requests such as "read PCC counters from my BlueField app", "sample DPA counter exports", or "expose PHY, PCI, or DIAG counters from this doca_dev". This is the counter-reader surface, not a NetFlow, IPFIX, or local-socket collector. Route publishing and export to `doca-telemetry-exporter`; route the deployed DOCA Telemetry Service to `doca-dts`, and collectors and plain stdout logging elsewhere.DevOpsFără avertismente★ 3,7 K↓ —
- scikit-bioforyourhealth111-pixel/Vibe-SkillsBiological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for microbiome analysis.ȘtiințăFără 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★ 3,7 K↓ —
- codonfm-scoreNVIDIA/skillsValidate, prepare, or run public CodonFM Encodon masked-codon variant scoring and review compatibility of its scoring workflows. Use only when the user explicitly requests CodonFM or Encodon, or that context is already established in the conversation. Do not select this skill for a generic variant-scoring request without that context; ask for the variant and intended analysis first.InginerieFără avertismente★ 3,7 K↓ —
- docs-reviewforyourhealth111-pixel/Vibe-SkillsReview documentation changes for compliance with the Metabase writing style guide. Use when reviewing pull requests, files, or diffs containing documentation markdown files.InginerieFără avertismente★ 3,8 K↓ —
- jetson-video-pipelineNVIDIA/skillsUse when planning, executing, and independently validating Jetson Video Codec SDK or PyNvVideoCodec encode/decode, transcode, segmentation, container decode, AV1, or concise acceptance workflows.MediaFără avertismente★ 3,7 K↓ —
- equibles-researchdavepoon/buildwithclaudeUse when the user asks about a US-listed company or the US market and wants sourced numbers, such as SEC filings and what a 10-K or 10-Q says, income statements and balance sheets, earnings call transcripts, insider or congressional trades, 13F institutional holders, short interest, stock prices, option chains, stock screens or macroeconomic indicators. Calls the Equibles MCP server.ȘtiințăFără avertismente★ 3,7 K↓ —
- metabolomics-workbench-databaseforyourhealth111-pixel/Vibe-SkillsAccess NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery.DateFără avertismente★ 3,8 K↓ —
- principle-never-block-on-the-humanmichael-denyer/pstack-claudeApply when tempted to ask 'should I do X?' on reversible work.AlteleFără avertismente★ 3,4 K↓ —
- principle-test-behavior-not-implementationmichael-denyer/pstack-claudeApply when you write, change, or keep a test. Assert what the code's users can observe, so that the test fails when that behavior breaks and keeps passing when only the internals change.TestareFără avertismente★ 3,4 K↓ —
- holoscan-module-lifecycleNVIDIA/skillsDevelop external Holoscan Modules with the Holoscan CLI and use them in Holoscan applications: scaffold, test, Python bindings, DEB/WHEEL packaging, and clean-consumer proof.TestareFără avertismente★ 3,7 K↓ —
- jetson-customize-mgbeNVIDIA/skillsEnable Jetson Thor 25G/10G/1G MGBE QSFP via kernel-DT overlay. Do NOT use for UPHY lane allocation or ODMDATA edits.RedactareFără avertismente★ 3,7 K↓ —
- jetson-derive-carrierNVIDIA/skillsBootstrap a custom carrier board by forking carrier files and scaffolding a DT overlay from the reference devkit. Use after jetson-init-source; not for module-level or kernel-DTB changes.AlteleFără avertismente★ 3,7 K↓ —
- pulumi-debug-failed-operationpulumi/agent-skillsDebug a Pulumi update or preview that failed: read the failure Pulumi already recorded, find what caused it, and fix it. Load this skill when the user asks to debug, diagnose, or fix a failed update or preview, or points at a failing `pulumi up` or `pulumi preview`. Don't load it for authoring new infrastructure, migrations, or provider upgrades; those have their own skills.OficialInginerieFără avertismente★ 78↓ —
- 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★ 3,7 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★ 3,7 K↓ —
tao-train-rtdetr
NVIDIA/skills
DevOpsActualizat alaltăieri
De la autor
RT-DETR (Real-Time DEtection TRansformer) for 2D object detection. Designed for real-time inference with competitive accuracy and supports distillation and quantization for deployment optimization. Use when training, evaluating, distilling, quantizing, exporting, or running inference for a TAO RT-DETR model. Trigger phrases include "train RT-DETR", "real-time DETR", "low-latency object detection", "RT-DETR distillation / quantization".
Instalare
npx skills add NVIDIA/skills --skill tao-train-rtdetr -a claude-code
Se instalează în .claude/skills/tao-train-rtdetr/ · 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 (25)
- BENCHMARK.md
- SKILL.md
- config/skillspector-baseline.yaml
- evals/evals.json
- references/skill_info.yaml
- references/spec_template_deploy_evaluate.yaml
- references/spec_template_deploy_gen_trt_engine.yaml
- references/spec_template_deploy_inference.yaml
- references/spec_template_distill.yaml
- references/spec_template_evaluate.yaml
- references/spec_template_export.yaml
- references/spec_template_inference.yaml
- încă 13