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 10 ore
45.602 skill-uri
- glassersickn33/agentic-awesome-skillsSearch, inspect, and run third-party data APIs through one CLI when the environment has no suitable integration.InginerieFără avertismente★ 48,5 K↓ —
- mobile-android-designwshobson/agentsMaster Material Design 3 and Jetpack Compose patterns for building native Android apps. Use when designing Android interfaces, implementing Compose UI, or following Google's Material Design guidelines.DesignFără avertismente★ 41,7 K↓ —
- design-system-patternswshobson/agentsBuild scalable design systems with design tokens, theming infrastructure, and component architecture patterns. Use when creating design tokens, implementing theme switching, building component libraries, or establishing design system foundations.DesignFără avertismente★ 41,7 K↓ —
- fastapi-templateswshobson/agentsCreate production-ready FastAPI projects with async patterns, dependency injection, and comprehensive error handling. Use when building new FastAPI applications or setting up backend API projects.InginerieFără avertismente★ 41,7 K↓ —
- gke-observabilitygoogle/skillsConfigures GKE observability, including Cloud Logging, Cloud Monitoring, and managed Prometheus. Use when configuring GKE monitoring, setting up GKE logging, or configuring Prometheus metrics collection, and to troubleshoot Managed Service for Prometheus (GMP) issues such as missing metrics, unhealthy scrape targets, PodMonitoring misconfiguration, rule/alert evaluation failures, and monitoring permission errors. Don't use to configure local application logging frameworks or external APMs outside GKE.OficialDevOpsFără avertismente★ 21,6 K↓ —
- polars-bioK-Dense-AI/scientific-agent-skillsPerforms genomic interval overlap, nearest, merge, coverage, complement and subtraction on Polars DataFrames, and reads or writes BED, VCF, BCF, BAM, CRAM, GFF, GTF, FASTA and FASTQ data. Use for coordinate-aware genomic joins, read-depth analysis, lazy bioinformatics I/O, SQL queries or migration from bioframe.DateFără avertismente★ 54,5 K↓ —
- gke-backup-drgoogle/skillsConfigures Backup for GKE: the BackupRestore cluster addon, BackupPlan and RestorePlan resources, restore workflows, and CMEK-encrypted backups. Use for backup policies, disaster recovery, or GKE cluster restores. Don't use for database backups.OficialDateFără avertismente★ 21,6 K↓ —
- create-readmegithub/awesome-copilotCreate a README.md file for the projectAlteleFără avertismente★ 40,4 K↓ —
- next-intl-add-languagegithub/awesome-copilotAdd new language to a Next.js + next-intl applicationAlteleFără avertismente★ 40,4 K↓ —
- google-cloud-scc-querygoogle/skillsQueries and retrieves active security findings, external exposures, toxic combinations, vulnerabilities, threats, and sensitive data risks from Security Command Center on Google Cloud. Use when retrieving details for a security finding by its name, validating finding scope (e.g., verifying findingClass is TOXIC_COMBINATION, VULNERABILITY, EXTERNAL_EXPOSURE, or THREAT), or fetching finding details for triage. Don't use to draft remediations, apply patches, or execute configurations.OficialSecuritateFără avertismente★ 21,6 K↓ —
- google-cloud-solution-hybrid-search-alloydbgoogle/skillsDiscovers requirements and generates architectural, design, and deployment guidance for dynamic hybrid search systems by combining semantic search and keyword search. Optimized for AlloyDB hybrid search use cases in Google Cloud. Use when users need vector search combined with structured SQL filtering, faceted attributes, semantic reranking, in-database AI validation, or serverless hosting across transactional relational databases, analytical data warehouses, or managed database engines. DON'T use this skill for simple keyword-only search, or when a standalone non-relational vector database is required.OficialDevOpsFără avertismente★ 21,6 K↓ —
- gitlab-ci-patternswshobson/agentsBuild GitLab CI/CD pipelines with multi-stage workflows, caching, and distributed runners for scalable automation. Use when implementing GitLab CI/CD, optimizing pipeline performance, or setting up automated testing and deployment.TestareFără avertismente★ 41,7 K↓ —
- pinecone-raggithub/awesome-copilotBuild production RAG pipelines and persistent agent memory using Pinecone as the vector database backend. ALWAYS USE THIS SKILL when the user mentions Pinecone, wants to index documents for semantic search, build a retrieval-augmented generation system, store agent memory across sessions, implement hybrid search, or connect an LLM to a searchable knowledge base — even if they don't say "Pinecone" explicitly. Also use when the user asks about vector databases for RAG, namespace isolation for multi-tenant agents, embedding pipelines, or scaling a knowledge base beyond what local storage can handle. DO NOT use for local-only vector stores (Chroma, FAISS, pgvector) or pure keyword search with no semantic component.DateFără avertismente★ 40,4 K↓ —
- github-issuesgithub/awesome-copilotCreate, update, and manage GitHub issues using MCP tools. Use this skill when users want to create bug reports, feature requests, or task issues, update existing issues, add labels/assignees/milestones, manage repository labels, set issue fields (dates, priority, custom fields), set issue types, manage issue workflows, link issues, add dependencies, or track blocked-by/blocking relationships. Triggers on requests like "create an issue", "file a bug", "request a feature", "update issue X", "set the priority", "set the start date", "create a label", "rename a label", "list repo labels", "link issues", "add dependency", "blocked by", "blocking", or any GitHub issue management task.ProductivitateFără avertismente★ 40,4 K↓ —
- agentic-evalgithub/awesome-copilotPatterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response qualityTestareFără avertismente★ 40,4 K↓ —
- accessibility-compliancewshobson/agentsImplement WCAG 2.2 compliant interfaces with mobile accessibility, inclusive design patterns, and assistive technology support. Use when auditing accessibility, implementing ARIA patterns, building for screen readers, or ensuring inclusive user experiences.JuridicFără avertismente★ 41,7 K↓ —
- arize-annotationgithub/awesome-copilotCreates and manages annotation configs (categorical, continuous, freeform label schemas) and annotation queues (human review workflows) on Arize. Applies human annotations to project spans via the Python SDK. Use when the user mentions annotation config, annotation queue, label schema, human feedback, bulk annotate spans, update_annotations, labeling queue, annotate record, or human review.InginerieFără avertismente★ 40,4 K↓ —
- k8s-manifest-generatorwshobson/agentsCreate production-ready Kubernetes manifests for Deployments, Services, ConfigMaps, and Secrets following best practices and security standards. Use when generating Kubernetes YAML manifests, creating K8s resources, or implementing production-grade Kubernetes configurations.DevOpsFără avertismente★ 41,7 K↓ —
- spark-optimizationwshobson/agentsOptimize Apache Spark jobs with partitioning, caching, shuffle optimization, and memory tuning. Use when improving Spark performance, debugging slow jobs, or scaling data processing pipelines.InginerieFără avertismente★ 41,7 K↓ —
- unity-ecs-patternswshobson/agentsMaster Unity ECS (Entity Component System) with DOTS, Jobs, and Burst for high-performance game development. Use when building data-oriented games, optimizing performance, or working with large entity counts.AlteleFără avertismente★ 41,7 K↓ —
- recipe-batch-invite-to-eventgoogleworkspace/cliAdd a list of attendees to an existing Google Calendar event and send notifications.ProductivitateFără avertismente★ 31,9 K↓ —
- cs-demand-gen-specialistalirezarezvani/claude-skills380 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 380+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8 more coding agents — engineering, marketing, product, compliance, C-level advisory, research, business operations, commercial & finance, and your daily productivity skills.PlanificareFără avertismente★ 28,7 K↓ —
- review-architecturepascalorg/editorReview a PR against the Pascal architectural rules — package boundaries (core/viewer/editor/nodes), the registry-driven composition model (def.geometry / def.renderer / def.system), legacy-dispatch regressions, the slots + world-scale-UV convention for new nodes/geometry, hook hygiene (useEditor/useScene/useViewer), and selector performance. Use when the user asks to review a PR, audit a branch, or check that changes respect the codebase's architecture.PlanificareFără avertismente★ 25,1 K↓ —
- recipe-review-overdue-tasksgoogleworkspace/cliFind Google Tasks that are past due and need attention.InginerieFără avertismente★ 31,9 K↓ —
optimize-for-gpu
K-Dense-AI/scientific-agent-skills
DateActualizat acum 7 zile
De la autor
GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster. Use for CUDA/GPU optimization; CPU-bound NumPy, SciPy, pandas, scikit-learn, NetworkX, scikit-image, vector-search, image-processing, graph, simulation, or file-I/O workloads; CuPy, cuDF, cuML, cuGraph, cuVS, cuCIM, KvikIO, Warp, Newton, Numba-CUDA, or RAFT questions; and profiling, memory-transfer, kernel, or multi-GPU bottlenecks. Also use when large data-parallel Python code is slow and GPU acceleration is a plausible option, even if the user does not name CUDA.
Instalare
npx skills add K-Dense-AI/scientific-agent-skills --skill optimize-for-gpu -a claude-code
Se instalează în .claude/skills/optimize-for-gpu/ · 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 95
Securitate100
Proveniență95
Întreținere100
Licență100
Adopție73
Fișiere (16)
- SKILL.md
- references/code_transformation_patterns.md
- references/cucim.md
- references/cudf.md
- references/cugraph.md
- references/cuml.md
- references/cupy.md
- references/cuspatial.md
- references/cuvs.md
- references/cuxfilter.md
- references/decision_framework.md
- references/installation.md
- încă 4