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 18 ore
44.573 de skill-uri
- complexa-targetNVIDIA/skillsAdd, edit, inspect, or validate Proteina-Complexa target definitions for protein binders, ligand binders, and AME motif scaffolding. Use for target registries, chain/residue selectors, hotspots, ligand fields, and incomplete motif inputs. Covers direct YAML edits and complexa target/validate target commands; running a campaign with an already registered target belongs to complexa-design.DesignFără avertismente★ 3,7 K↓ —
- tao-train-nvpanoptix3dNVIDIA/skillsNVPanoptix3D for panoptic 3D scene reconstruction from posed RGB images. Produces 3D panoptic segmentation (semantic, instance, and panoptic masks) with occupancy completion. Built on a VGGT backbone with a Mask2Former-style head and 3D frustum reconstruction. Use when training, evaluating, exporting, or running inference for a TAO NVPanoptix3D model. Trigger phrases include "train NVPanoptix3D", "panoptic 3D reconstruction", "3D scene segmentation", "occupancy completion".AlteleFără avertismente★ 3,7 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★ 3,7 K↓ —
- 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-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★ 3,7 K↓ —
- jetson-print-bsp-infoNVIDIA/skillsUse when you need to print Jetson BSP info (L4T version, board configs, rootfs state) from a Linux_for_Tegra root on the host PC. This is an example skill.AlteleFără avertismente★ 3,7 K↓ —
- i4h-workflow-validateNVIDIA/skillsRun the root-level workflow runtime policy or rule-based rollouts and verify simulator success. Use for evaluation, checkpoints, or local controllers; do not use for replay or dataset annotation.ProductivitateFără avertismente★ 3,7 K↓ —
- jetson-customize-pcieNVIDIA/skillsPer-controller PCIe enable / disable / lanes / link-speed for a Jetson Thor or Orin custom carrier via ODMDATA + kernel-DT overlay. Do NOT use for UPHY lane allocation or endpoint-mode bring-up.AlteleFără avertismente★ 3,7 K↓ —
- tao-train-pointpillarsNVIDIA/skillsPointPillars for 3D object detection from LiDAR point clouds. Encodes point clouds into a pseudo-image via a pillar-based representation, then applies 2D detection — used in autonomous driving and robotics. Use when training, evaluating, exporting, pruning, retraining, or running inference for a TAO PointPillars model. Trigger phrases include "train PointPillars", "LiDAR 3D detection", "point-cloud object detection", "pillar-based 3D detector".MediaFără avertismente★ 3,7 K↓ —
- earth2studio-discoverNVIDIA/skillsFind Earth2Studio models, data sources, and examples for a weather/climate use case. Do NOT use for writing inference code, downloading data, or installation.RedactareFără avertismente★ 3,7 K↓ —
- doca-flow-grpc-serverNVIDIA/skillsRemote control of DOCA Flow over gRPC with the shipped `doca_flow_grpc` server: program Flow pipes and entries from Python, Go, Rust or Java, or from another host, instead of linking `libdoca_flow.so`. PLAINTEXT-ONLY: the server uses `grpc::InsecureServerCredentials()` with NO TLS / mTLS / token-auth knob; transport security must come from external infrastructure (e.g. an mTLS proxy / sidecar) on a trusted segment. Trigger even without "gRPC": "program Flow rules from Python on another host", "remotely configure pipes on the BlueField", "client times out connecting to the Flow server", "where is the .proto for Flow", "UNAUTHENTICATED / FAILED_PRECONDITION on a Flow RPC". Covers bringing up, configuring, hardening and debugging the server. Route elsewhere for the underlying doca-flow C API, generic gRPC tooling (protoc, language bindings), or DOCA install / BFB bring-up.SecuritateFără avertismente★ 3,7 K↓ —
- doca-sha-offload-engineNVIDIA/skillsUse this skill when wiring the DOCA SHA Offload Engine (an OpenSSL ENGINE) into an existing OpenSSL pipeline to offload one-shot SHA-1, SHA-256, or SHA-512 (EVP_Digest) onto DOCA SHA hardware without rewriting against doca-sha. Covers engine load mechanics (`openssl engine dynamic`, `set_pci_addr` ctrl, `-engine_impl`), the SHA-224 negative test that proves offload engaged, the message-size window where offload beats CPU SHA, and engine-vs-library selection. Trigger even when the user does not say "DOCA SHA Offload Engine" or "OpenSSL ENGINE" — typical implicit phrasings: "speed up openssl SHA on BlueField", "offload SHA without code changes", "is openssl using the accelerator or falling back to software", "prove DOCA SHA actually ran", "openssl dgst hashed but I'm not sure it was offloaded". Refuse and route elsewhere for new SHA pipelines (use doca-sha), MD5 / SHA-3 / SHA-224 / HMAC-SHA offload, incremental hashing via chained `EVP_DigestUpdate`, or OpenSSL PROVIDER authoring.TestareFără 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★ 3,7 K↓ —
- gsd:statsdavepoon/buildwithclaudeDisplay project statistics — phases, plans, requirements, git metrics, and timelinePlanificareFără avertismente★ 3,7 K↓ —
- nemo-retriever-mcpNVIDIA/skillsUse when a task needs to search or add documents through NeMo Retriever MCP.ProductivitateFără avertismente★ 3,7 K↓ —
- 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★ 3,7 K↓ —
- tao-train-segformerNVIDIA/skillsSegFormer for semantic segmentation. Lightweight transformer-based architecture with hierarchical feature extraction, efficient for real-time segmentation tasks. Use when training, evaluating, exporting, quantizing, or running inference for a TAO SegFormer model. Trigger phrases include "train SegFormer", "semantic segmentation", "lightweight transformer segmenter", "real-time semantic segmentation".PlanificareFără avertismente★ 3,7 K↓ —
- jetson-quick-startNVIDIA/skillsEntry skill for Jetson / IGX BSP customization. Asks one core click-to-select setup questionnaire and passes prefilled answers to downstream setup skills.AlteleFără avertismente★ 3,7 K↓ —
- jetson-init-targetNVIDIA/skillsAuthor a new Jetson target-platform profile (reference_devkit + optional custom_carrier) and update the active pointer. Use to create a target; not for switching existing profiles.AlteleFără avertismente★ 3,7 K↓ —
- doca-flow-dpa-perfNVIDIA/skillsUse this skill when the user is invoking doca_flow_dpa_perf on DPA-capable hardware (ConnectX-7 minimum supported, ConnectX-8 recommended, or BlueField-3) to measure rule update / disable rates on the DPA-offloaded DOCA Flow path — picking the active / passive device split, choosing workload-shape axes (burst, queue, completion threshold, workers, hash pipe algo, PSL tables), or reading Kops/sec iteration stats and the optional self-test. Trigger even when the user does not explicitly mention "doca_flow_dpa_perf" or "DPA Provider" — typical implicit phrasings include "how fast can the DPA program path-selector entries", "baseline rule-update rate on ConnectX-8", "tool reports zero ops on my BlueField", "self-test sentinel never shows on tcpdump", or "is my BlueField-2 DPA-capable". Refuse and route elsewhere for the host / DPU-CPU Flow path (doca-flow-perf), Flow pipeline tuning (doca-flow-tune), writing doca-flow / doca-dpa applications, or DOCA install — those belong to other skills.TestareFără avertismente★ 3,7 K↓ —
- foundationpose-pipelineNVIDIA/skillsAdapt BOP datasets, run the FoundationPose perception pipeline with TAO depth, and evaluate or re-score pose results. Use for dataset runs and result comparisons; environment installation belongs to foundationpose-setup.AlteleFără avertismente★ 3,7 K↓ —
- nemo-retrieverNVIDIA/skillsUse when searching, extracting, ingesting, or querying a document collection with the NeMo Retriever 26.8.1 CLI, including local LanceDB indexes and deployed Retriever services. Use for PDFs, images, Office files, HTML, text, audio, and video; not for editing documents or web search.DevOpsFără avertismente★ 3,7 K↓ —
- mcore-split-prNVIDIA/skillsSplit a PR into multiple PRs to reduce the number of required CODEOWNERS reviewer groups.AlteleFără avertismente★ 3,7 K↓ —
- doca-flow-perfNVIDIA/skillsUse this skill when the user measures control-plane insertion throughput of DOCA Flow with the doca_flow_perf binary on x86 host or Arm cores — selecting a configs/ JSON policy, weighing the DPDK-versus-DOCA backend, running the smoke iteration then the eval loop, interpreting CPU cycles plus num_pushed / num_failed, or capturing the four-tuple (DOCA release, firmware, JSON policy, worker config) that makes an insertion figure defensible. Also load it for implied asks like "5-tuple hairpin insert figure", "flow-perf result mismatches release notes", "DPDK-vs-DOCA comparison", or "install variance too high". Refuse and route to the proper owner for live-app optimization (doca-flow-tune), DPA-side measurement (doca-flow-dpa-perf), wire throughput or latency, or library-internal pipe semantics.PlanificareFără avertismente★ 3,7 K↓ —
gsd:add-tests
davepoon/buildwithclaude
TestareActualizat ieri
De la autor
Generate tests for a completed phase based on UAT criteria and implementation
Instalare
npx skills add davepoon/buildwithclaude --skill gsd:add-tests -a claude-code
Se instalează în .claude/skills/gsd-add-tests/ · 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: MIT
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 90
Securitate100
Proveniență83
Întreținere100
Licență100
Adopție57
Fișiere (1)
- SKILL.md