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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 3 ore
48.168 de skill-uri
- brevo-automationdavepoon/buildwithclaudeAutomate Brevo (Sendinblue) tasks via Rube MCP (Composio): manage email campaigns, create/edit templates, track senders, and monitor campaign performance. Always search tools first for current schemas.MarketingFără avertismente★ 3,7 K↓ —
- gsd:list-phase-assumptionsdavepoon/buildwithclaudeSurface Claude's assumptions about a phase approach before planningPlanificareFără avertismente★ 3,7 K↓ —
- nemo-mbridge-resiliencyNVIDIA/skillsResiliency features in Megatron Bridge including fault tolerance, straggler detection, in-process restart, preemption, and re-run state machine.AlteleFără avertismente★ 3,8 K↓ —
- neurokit2foryourhealth111-pixel/Vibe-SkillsComprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable for heart rate variability analysis, event-related potentials, complexity measures, autonomic nervous system assessment, psychophysiology research, and multi-modal physiological signal integration.ȘtiințăFără avertismente★ 3,8 K↓ —Apare și în 1 alt depozit
- participation-warmup-planneraaron-he-zhu/aaron-marketing-skillsUse when the user asks to "plan the participation ramp before we promote", "how much account history or karma do we need in this community", or "design entry incentives and member lifecycle for our own Discord"; produces the per-community pre-promotion warming plan — account-history/tenure expectations (Estimated, named sources), a give-before-ask ledger spec, a per-community etiquette + rule digest with last-verified dates, and the warming → active graduation criteria that channel-registry requires as state-transition evidence — plus the owned-community variant (entry paths + member lifecycle for your own Discord/Slack/forum/企业微信私域). Not for launch-day submissions or T-0 threads — use community-launch-runner. 社区预热/先给后取/账号养成/毕业标准PlanificareFără avertismente★ 3 K↓ —
- nemo-rl-auto-researchNVIDIA/skillsAutonomous NeMo-RL research agent workflow for directed hypothesis testing and open-ended discovery. Guides agents through the full experiment lifecycle: understanding recipes and environments, wiring RL or NeMo-gym runs, launching reproducible baselines and iterations, analyzing results, preserving human oversight, and using git plus TSV logs as the research ledger. Do NOT use for: bug fixes, code review, documentation, refactoring, dependency updates, or single-file changes.ȘtiințăFără avertismente★ 3,8 K↓ —
- garden-inboxpaperclipai/paperclipScan a Paperclip user's Mine inbox, classify reversible archive candidates, request checkbox confirmation, and archive only accepted selections. Use when asked to garden, clean up, prune, or tidy a Paperclip inbox without changing issues, branches, or workspaces.AlteleFără avertismente★ 109,2 K↓ —
- principle-experience-firstbacknotprop/pstackApply when product, UX, or feature-scope tradeoffs come up. Choose user delight over implementation convenience; ship fewer polished features over more rough ones.DesignFără avertismente★ 3,3 K↓ —Apare și în 3 alte depozite
- clerk-androidclerk/skillsImplement Clerk authentication for native Android apps using Kotlin and Jetpack Compose with clerk-android source-guided patterns. Use for prebuilt AuthView/UserButton or custom API-driven auth flows. Do not use for Expo or React Native projects.OficialInginerieFără avertismente★ 89↓ —
- nemotron-customizeNVIDIA/skillsPlan, configure, and chain repo-native Nemotron customization steps into single-step or multi-step pipelines: curation, translation, SFT/PEFT (AutoModel or Megatron-Bridge), pretraining/CPT, RL alignment (DPO/RLVR/GRPO/RLHF), BYOB/MCQ benchmarks, checkpoint conversion, ModelOpt optimization, env profiles, and evaluation of trained checkpoints or existing/hosted endpoints. Use when a request names a Nemotron step or workflow, or asks to clean, translate, train, fine-tune, align, convert, optimize, evaluate, or compose these into a pipeline. Do NOT use for frontend/dashboard/visualization work, generic ML advice, billing/access, or non-Nemotron coding tasks.DesignFără avertismente★ 3,8 K↓ —
- principle-model-the-domainbacknotprop/pstackApply when writing stateful logic, or when code branches a lot or repeats a shape assumption across files.RedactareFără avertismente★ 3,3 K↓ —Apare și în 1 alt depozit
- doca-flow-tuneNVIDIA/skillsUse this skill when the user is tuning a live or captured `doca-flow` pipeline with `doca_flow_tune` — snapshotting pipe / counter / KPI state, picking a tuning axis (rule placement, resource hints / table sizing, HW-offload mode) and a matching measurement (rule-install rate, lookup latency, hardware-counter delta), running offline or online (read-only or state-changing) modes, reading the dumper CSV / analyze JSON / visualize mermaid, or applying a recommendation back into the Flow program. Trigger even when the user does not explicitly mention "doca_flow_tune" — typical implicit phrasings include "Flow rule-install rate is low on BlueField", "table sizing looks wrong for this pipe", "tune visualize step is empty", "before/after counters don't move", or "which doca-flow knob does this recommendation hit". Refuse and route elsewhere for writing the doca-flow application, DOCA install, or streaming Flow telemetry — those belong to other skills.DateFără avertismente★ 3,8 K↓ —
- tao-train-rtdetrNVIDIA/skillsRT-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".DevOpsFără avertismente★ 3,8 K↓ —
- interrogatebacknotprop/pstackUse for "interrogate", "adversarial review", "multi-model review", "challenge this", "stress test this code", "find blind spots", or "tear this apart". Adversaries try to break a change or design, and only findings proven by a run survive.TestareFără avertismente★ 3,3 K↓ —
- jetson-generate-kbNVIDIA/skillsBuild a per-target knowledge-base markdown next to the active profile by walking the BSP root and source tree. Use after init-image / init-source; not for editing profile fields.MediaFără avertismente★ 3,8 K↓ —
- in-your-own-wordsbacknotprop/pstackRestate in your own words what you think the user's goals are and what problem they're trying to solve. Use for /in-your-own-words.AlteleFără avertismente★ 3,3 K↓ —
- principle-encode-lessons-in-structurebacknotprop/pstackApply when you catch yourself writing the same instruction a second time, or notice a recurring correction. Encode the rule as a lint, metadata flag, runtime check, or script instead of more text.RedactareFără avertismente★ 3,3 K↓ —Apare și în 1 alt depozit
- upstream-patchespulumi/agent-skillsCreate, amend, remove, and rebase patches for Terraform provider submodules using `./scripts/upstream.sh`. Use when `upgrade-provider` or manual patch work needs owning-patch lookup, patch conflict fixes, patch/hunk removal, or upstream rebase.OficialDevOpsFără avertismente★ 78↓ —
- pulumi-best-practicespulumi/agent-skillsLoad when the user is writing, reviewing, or debugging Pulumi TypeScript/Python programs; asks about Output<T> or apply() usage; wants to create ComponentResource classes; needs to refactor resources without destroying them (aliases); is setting up secrets or config; or is configuring a pulumi preview/up CI workflow. Also load for questions about resource dependency order, parent/child resource relationships, or pulumi.interpolate.OficialRedactareFără avertismente★ 78↓ —
- 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↓ —
- cloudformation-to-pulumipulumi/agent-skillsConvert, migrate, or import AWS CloudFormation stacks or templates into Pulumi programs. Load this skill whenever a user wants to move from CloudFormation to Pulumi, convert a CFN template, import existing CloudFormation-managed resources into Pulumi, or asks about CloudFormation-to-Pulumi migration in any form. Also load when the user mentions cdk-importer in a migration context.OficialDevOpsFără avertismente★ 78↓ —
- pulumi-componentpulumi/agent-skillsGuide for authoring Pulumi ComponentResource classes. Use when creating reusable infrastructure components, designing component interfaces, setting up multi-language support, or distributing component packages.OficialDevOpsFără avertismente★ 78↓ —
- pulumi-upgrade-providerpulumi/agent-skillsAutomate Pulumi provider repo upgrades with the `upgrade-provider` tool. Use when upgrading a pulumi provider repository to a new upstream version, running `upgrade-provider`, and addressing its common failure modes like patch conflicts or missing module mappings.OficialAlteleFără avertismente★ 78↓ —
- lobsterdomainsdavepoon/buildwithclaudeRegister ICANN domains with crypto payments (USDC/USDT/ETH/BTC) via API — built for AI agentsFinanțeFără avertismente★ 3,7 K↓ —
physicsnemo-shard-tensor
NVIDIA/skills
De la autor
Official NVIDIA-authored guidance for PhysicsNeMo ShardTensor domain parallelism — integrate domain parallelism into training/inference scripts (new or existing) with DDP or FSDP2, write and register shard patches to enable new layers/ops, and bootstrap multi-GPU correctness tests. Use when working with ShardTensor, scatter_tensor, domain parallelism, sequence/spatial sharding, ring attention, DeviceMesh + DDP/FSDP2 hybrid parallelism, or physicsnemo.domain_parallel. Do NOT use for generic PyTorch DDP/FSDP setup without domain parallelism, picking a PhysicsNeMo model or example (use physicsnemo-discover), or non-distributed training questions.
Instalare
npx skills add NVIDIA/skills --skill physicsnemo-shard-tensor -a claude-code
Se instalează în .claude/skills/physicsnemo-shard-tensor/ · 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
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De ce 90
Fișiere (8)
- BENCHMARK.md
- SKILL.md
- evals/evals.json
- references/integration-checklist.md
- references/new-op-patterns.md
- references/testing.md
- skill-card.md
- skill.oms.sig