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.
47.307 skill-uri din 2.272 de depozite · actualizat acum 9 ore
46.198 de skill-uri
- gsd:cleanupdavepoon/buildwithclaudeArchive accumulated phase directories from completed milestonesAlteleFără avertismente★ 3,7 K↓ —
- gsd:add-testsdavepoon/buildwithclaudeGenerate tests for a completed phase based on UAT criteria and implementationTestareFără avertismente★ 3,7 K↓ —
- drill-medavepoon/buildwithclaudeTeach the user a topic as an adaptive tutor — retrieval practice, spaced repetition with decay, and persistent memory in ~/.drill-me/. Use when the user wants to learn or be drilled on something, says "drill me on X", "teach me X", or wants to study a topic, a codebase, or a document.ProductivitateFără avertismente★ 3,7 K↓ —
- gsd:managerdavepoon/buildwithclaudeInteractive command center for managing multiple phases from one terminalAlteleFără avertismente★ 3,7 K↓ —
- 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★ 3,8 K↓ —
- gsd:from-gsd2davepoon/buildwithclaudeImport a GSD-2 (.gsd/) project back to GSD v1 (.planning/) formatPlanificareFără 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★ 3,8 K↓ —
- gsd:threaddavepoon/buildwithclaudeManage persistent context threads for cross-session workProductivitateFără avertismente★ 3,7 K↓ —
- gsd:sketchdavepoon/buildwithclaudeSketch UI/design ideas with throwaway HTML mockups, or propose what to sketch next (frontier mode)DesignFără avertismente★ 3,7 K↓ —
- tao-train-mask2formerNVIDIA/skillsMask2Former for universal image segmentation (panoptic, instance, and semantic). Transformer-based with masked attention for high-quality segmentation results. Use when training, evaluating, exporting, quantizing, or running inference for a TAO Mask2Former model. Trigger phrases include "train Mask2Former", "universal segmentation", "panoptic / instance / semantic segmentation", "masked-attention transformer segmenter".MediaFără avertismente★ 3,8 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★ 3,8 K↓ —
- gsd:reviewdavepoon/buildwithclaudeRequest cross-AI peer review of phase plans from external AI CLIsInginerieFără avertismente★ 3,7 K↓ —
- gsd:importdavepoon/buildwithclaudeIngest external plans with conflict detection against project decisions before writing anything.RedactareFără avertismente★ 3,7 K↓ —
- recapdavepoon/buildwithclaudeTriggered by "monthly recap", "how did I do this month", "spending summary", "financial review", "weekly recap", "quarterly review", "year in review"FinanțeFără avertismente★ 3,7 K↓ —
- doca-hardware-safetyActualizatNVIDIA/skillsUse this skill whenever the agent is about to recommend or apply a change that touches DPU / NIC hardware state on a live system — mlxconfig firmware-parameter write, NIC firmware burn, BFB reflash, NIC ↔ DPU mode flip, SR-IOV or device-emulation slot enable, kernel boot-parameter change (IOMMU, hugepages, VFIO), PCIe rebind / rescan / link-state flip, BlueField cold reboot, or remediation of a BlueField thermal shutdown. Wrap the change in pre-flight inventory, OOB reachability, a maintenance window, replica rehearsal, and rollback. Trigger on implicit phrasing: "flip BlueField mode over SSH", "enable SR-IOV and reboot", "burned firmware but mlxconfig shows old value", "BlueField thermal shutdown". Not for read-only inventory or version queries (doca-version, doca-caps). Refuse orientation (doca-public-knowledge-map), install or env debug (doca-setup), and program-side debug (doca-debug, doca-programming-guide).RedactareFără avertismente★ 3,8 K↓ —
- tao-train-oneformerNVIDIA/skillsOneFormer for universal image segmentation. Unifies panoptic, instance, and semantic segmentation with a single architecture using task-conditioned queries. Use when training, evaluating, exporting, quantizing, or running inference for a TAO OneFormer model. Trigger phrases include "train OneFormer", "universal segmentation", "task-conditioned segmentation", "panoptic / instance / semantic in one model".MediaFără avertismente★ 3,8 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↓ —
- gsd:plant-seeddavepoon/buildwithclaudeCapture a forward-looking idea with trigger conditions — surfaces automatically at the right milestonePlanificareFără 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★ 3,8 K↓ —
- tao-finetune-clipNVIDIA/skillsCLIP vision-language model for image-text retrieval, zero-shot classification, embedding extraction, ONNX export, and TensorRT deployment. Use when fine-tuning or training CLIP, running zero-shot classification, computing image embeddings, or deploying CLIP to ONNX/TensorRT. This is a single-action model skill; do not use it for an iterative weak-attribute improvement loop that keeps retraining and evaluating until progress stops, which belongs to tao-run-deft-pas.DevOpsFără avertismente★ 3,8 K↓ —
- mcore-split-prNVIDIA/skillsSplit a PR into multiple PRs to reduce the number of required CODEOWNERS reviewer groups.AlteleFără avertismente★ 3,8 K↓ —
- distilldavepoon/buildwithclaudeSynthesize wiki pages from related memories. One endpoint, one flow: daemon clusters and synthesizes what it can; agent finishes whatever the daemon couldn't (no LLM or cluster too big). Invoked as `/distill [target]`.AlteleFără avertismente★ 3,7 K↓ —
- doca-flowActualizatNVIDIA/skillsDOCA Flow packet steering on NVIDIA NICs/DPUs, linked into a C application: match/action pipes, ports, representors, forwarding, hairpin, counters. Trigger on packet steering, classifier, rule-matching, representor, hairpin or 5-tuple-to-queue questions even when "DOCA Flow" is not named. Also covers pipe validation before hardware programming, Flow/DOCA version match, and Flow API errors. First app: follow the local bundle (doca-setup, doca-programming-guide, doca-flow, doca-public-knowledge-map). Stage 1 pull nvcr.io/nvidia/doca/doca (NGC catalog tag, never invent); Stage 2 needs a real NIC. Then ls samples inside the container; never emit main.c, a Dockerfile, or hand-typed -l flags. Route software-only host pipelines, plain DPDK `rte_flow`, kernel TC, OVS, BFB bring-up, and DPU OS installation elsewhere. DPU OS installation is destructive and always requires explicit confirmation.InginerieFără avertismente★ 3,8 K↓ —
- doc-coauthoringanthropics/skillsGuide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.OficialRedactareFără avertismente★ 184,4 K↓ —Apare și în 6 alte depozite
pyopenms
foryourhealth111-pixel/Vibe-Skills
DateActualizat acum 3 zile
De la autor
Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal processing, feature detection, peptide identification, and quantitative analysis. Apply when working with mass spectrometry data, analyzing proteomics experiments, or processing metabolomics datasets.
Instalare
npx skills add foryourhealth111-pixel/Vibe-Skills --skill pyopenms -a claude-code
Se instalează în .claude/skills/pyopenms/ · 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 instrucțiuniFolosește rețeauaLicență: APACHE-2.0
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 90
Securitate100
Proveniență83
Întreținere100
Licență100
Adopție57
Fișiere (7)
- SKILL.md
- references/data_structures.md
- references/feature_detection.md
- references/file_io.md
- references/identification.md
- references/metabolomics.md
- references/signal_processing.md