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.
47.966 de skill-uri din 2.309 depozite · actualizat acum 4 ore
47.966 de skill-uri
- 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↓ —
- jetson-video-capabilityNVIDIA/skillsUse when Jetson codec, profile, chroma, bit-depth, dimension, engine-count, or operational support must be reconciled from live APIs, authenticated NVIDIA samples, and NVIDIA documentation; also applies the content-DRM scope.MediaFără avertismente★ 3,8 K↓ —
- trend-spotteraaron-he-zhu/aaron-marketing-skillsUse when the user asks to "find trending topics", "what trends should my brand jump on", or "time a campaign around a cultural moment"; produces a ranked trend report with brand-fit scores, format calls (rising/peak/declining), a cultural calendar, and go/skip recommendations. Not for finding the creators to run those trends — use influencer-discovery; not for building the brand posting calendar from a go verdict — use social-calendar-builder. 热点趋势洞察/借势营销MarketingFără avertismente★ 3 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↓ —
- budget-pacing-monitoraaron-he-zhu/aaron-marketing-skillsUse when the user asks to "check pacing", "am I over/under-spending", "is this campaign on track to hit budget", or "why did spend spike/stall mid-flight"; returns a spend-vs-target-curve read, learning-phase status, an over/under-delivery call, and a reallocation trigger. Not for initial budget allocation — use budget-optimizer; not for choosing the bid strategy — use bid-strategy-planner; not for the RQS gate — use ad-account-auditor. 付费广告预算节奏监控/跑量过快过慢/在途配速MarketingFără avertismente★ 3 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★ 3,8 K↓ —
- claude-md-reviewwesammustafa/Claude-Code-Everything-You-Need-to-KnowAudit a CLAUDE.md file for the patterns that actually degrade Claude Code's output — vagueness, unnamed files, stale facts, and bloat. Use when asked to review, audit, improve, shrink, or fix a CLAUDE.md, and when a project's results feel inconsistent or Claude keeps rediscovering the same context.InginerieFără avertismente★ 3,5 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↓ —
- 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↓ —
- performanceplugin87/ux-ui-agent-skillsOptimize UI performance against Core Web Vitals (LCP, INP, CLS) with loading/code-split strategy, layout-shift prevention, and animation performance rules. Use when the user wants to improve speed, fix jank or layout shift, hit Web Vitals budgets, or make a UI feel fast on low-end devices.DesignFără avertismente★ 3,1 K↓ —
- youtube-automationdavepoon/buildwithclaudeAutomate YouTube tasks via Rube MCP (Composio): upload videos, manage playlists, search content, get analytics, and handle comments. Always search tools first for current schemas.DateFără avertismente★ 3,7 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↓ —
- nemo-retriever-mcpNVIDIA/skillsUse when a task needs to search or add documents through NeMo Retriever MCP.ProductivitateFără avertismente★ 3,8 K↓ —
- skill-content-strategyZJU-REAL/Easel制定全面的内容策略方案:内容支柱架构、受众路径规划、90 天节奏原则、分发渠道策略、KPI 体系,输出可执行的策略文档。 当用户说"内容策略""策略方案""内容规划""怎么做内容""内容支柱""增长策略""涨粉策略"时使用。 元策略层,只出框架不出具体排期表(排期用 skill-content-calendar)。ProductivitateFără avertismente★ 4,2 K↓ —
- skill-strategy-advisorZJU-REAL/Easel基于现有内容数据和画像迭代优化内容策略。分析过去一段时间的内容表现、画像信息、 行业趋势,给出下一阶段的内容方向调整、新赛道建议、内容形式优化、发布节奏调整、 画像微调等策略建议。当用户说"下一步怎么做"、"策略建议"、"怎么调整"、"内容方向"、 "下个月策略"、"优化建议"、"迭代方向"时触发。 和 skill-content-strategy 的区别:content-strategy 从零制定策略, strategy-advisor 基于现有数据做迭代优化。AlteleFără avertismente★ 4,2 K↓ —
- beadsjeremylongshore/tons-of-skills-marketplaceUse when working in a repository that uses bd or Beads for durable project task tracking, issue dependencies, blocker management, multi-session handoff, or shared work memory. Trigger when the user asks to find ready work, claim or close tasks, create follow-up work, inspect blockers, recover project context, or choose between local planning and persistent project tracking.PlanificareFără avertismente★ 2,9 K↓ —Apare și în 2 alte depozite
- clari-install-authjeremylongshore/tons-of-skills-marketplaceConfigure a least-privilege Clari identity and validate Revenue API or Copilot credentials without exposing secrets. Use when starting an integration or rotating access. Trigger with: "set up Clari auth", "configure a Clari token", "test Copilot credentials".TestareFără avertismente★ 2,9 K↓ —
- kavel-image-studiodavepoon/buildwithclaudeTurn a photo into a specific AI look (new hairstyle, collectible figurine, royal pet portrait, wedding photo, 90s yearbook, sticker, HD restore) or a photo into a dance video, using Kavel (www.kavel.ai). Use when the user wants to restyle/transform a photo, asks "how do I make an AI X from my photo", or wants a photorealistic image edit that keeps the same face. Gives the right tool, a model-tuned prompt, and the generate link.MediaFără avertismente★ 3,7 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↓ —
- kiro-spec-tasksgotalab/cc-sddGenerate implementation tasks for a specificationPlanificareFără avertismente★ 3,7 K↓ —
- dropbox-automationdavepoon/buildwithclaudeAutomate Dropbox file management, sharing, search, uploads, downloads, and folder operations via Rube MCP (Composio). Always search tools first for current schemas.AlteleFără avertismente★ 3,7 K↓ —
- skill-kuaishou-uploadZJU-REAL/Easel快手视频发布:把竖版短视频发布到快手创作者中心。当用户说"发快手""上传快手""快手投稿" "发布到快手""快手视频发布"时使用。基于通用浏览器发布框架(Playwright + 登录态持久化)。TestareFără avertismente★ 4,2 K↓ —
- skill-channels-uploadZJU-REAL/Easel微信视频号发布:把竖版短视频发布到微信视频号(channels.weixin.qq.com)。当用户说 "发视频号""上传视频号""视频号发布""发到微信视频号""视频号投稿"时使用。基于通用浏览器 发布框架(Playwright + 登录态持久化),微信扫码登录。TestareFără avertismente★ 4,2 K↓ —
- gsd:execute-phasedavepoon/buildwithclaudeExecute all plans in a phase with wave-based parallelizationPlanificareFără avertismente★ 3,7 K↓ —
tao-train-mask-auto-label
NVIDIA/skills
De la autor
MAL (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".
Instalare
npx skills add NVIDIA/skills --skill tao-train-mask-auto-label -a claude-code
Se instalează în .claude/skills/tao-train-mask-auto-label/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
La ce are acces
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 90
Fișiere (14)
- BENCHMARK.md
- SKILL.md
- config/skillspector-baseline.yaml
- evals/evals.json
- references/skill_info.yaml
- references/spec_template_evaluate.yaml
- references/spec_template_inference.yaml
- references/spec_template_train.yaml
- schemas/evaluate.schema.json
- schemas/inference.schema.json
- schemas/manifest.json
- schemas/train.schema.json
- încă 2