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.
38.957 de skill-uri din 1.786 de depozite · actualizat acum 3 minute
38.957 de skill-uri
- google-cloud-waf-operational-excellencegoogle/skillsGenerates operational guidance for CI/CD deployment pipelines, observability, monitoring, logging, and incident management on Google Cloud based on the design principles and recommendations in the Operational Excellence pillar of the Google Cloud Well-Architected Framework (WAF). Use when the user asks about operations-related topics like capacity management, change management, incident and problem management, configuration management, deployment automation using infrastructure as code (IaC), or operational health checks for Google Cloud workloads.OficialDevOpsFără avertismente★ 21,5 K↓ —
- gke-ai-troubleshooting-tpu-vm-repair-stuckgoogle/skillsDiagnose GKE TPU VM instances stuck in Compute Engine repair (REPAIRING state) after host errors, maintenance events, or faulty host reports in single-host, multi-host, dynamic slicing, and TPU All Capacity mode node pools. Use when TPU instances in a slice node pool remain in REPAIRING, host error events appear in audit logs, or TPU slices are unschedulable due to a VM in repair. Don't use for nodes reporting Ready: Unknown when no VM is in REPAIRING (use gke-ai-troubleshooting-node-unresponsive-timeout), other NotReady nodes when no VM is in REPAIRING (use gke-node-notready), Pending Pods when all nodes are Ready (use gke-workload-troubleshooting), JobSet preemption events (use gke-ai-troubleshooting-jobset-interruption), or Slice custom resource lifecycle failures (use gke-ai-troubleshooting-tpu-dynamic-slices-monitoring).OficialAlteleFără avertismente★ 21,5 K↓ —
- aws-vpcsickn33/agentic-awesome-skillsDesign and implement VPCs and networking. Configure subnets, route tables, and security groups. Use when setting up AWS network infrastructure.DevOpsFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- cloud-logging-cross-project-configurationgoogle/skillsConfigure and troubleshoot Google Cloud cross-project centralized logging and read-time aggregation. Use when: - Setting up log routing from multiple projects/folders/organizations to a central log bucket. - Creating cross-project log sinks and configuring central log buckets. - Troubleshooting cross-project routing. Don't use for single-project basic configurations.OficialAlteleFără avertismente★ 21,5 K↓ —
- refactorgithub/awesome-copilotSurgical code refactoring to improve maintainability without changing behavior. Covers extracting functions, renaming variables, breaking down god functions, improving type safety, eliminating code smells, and applying design patterns. Less drastic than repo-rebuilder; use for gradual improvements.InginerieFără avertismente★ 40,4 K↓ —Apare și în 1 alt depozit
- google-cloud-solution-build-deploy-agentsgoogle/skillsDesigns, builds, and deploys AI agents or multi-agent systems on Google Cloud. Provides an interactive workflow to gather requirements, recommend a tailored architecture, and generate deployment instructions. Use when designing or implementing agentic systems on Google Cloud. Don't use for general Google Cloud solution architecture (use google-cloud-solution-architecture instead) or for narrow tasks targeting a single product without agent context.OficialDevOpsFără avertismente★ 21,5 K↓ —
- loopysickn33/agentic-awesome-skillsDiscover, find, compare, audit, repair, adapt, craft, run, debrief, and prepare repeatable AI-agent loops for publication.AlteleFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- gh-imagesickn33/agentic-awesome-skillsUpload local images to GitHub and get canonical user-attachments embed URLs; use when asked to attach a screenshot to a PR, issue, or comment, or to embed before/after images in a README.MediaFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- dailysickn33/agentic-awesome-skillsDocumentation and capabilities reference for DailyAlteleFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- cloud-monitoring-list-time-series-requestgoogle/skillsGenerates valid Cloud Monitoring ListTimeSeries requests and aggregation specifications from metric descriptors and resource parameters. Use when asked to create, generate, format, or build ListTimeSeries requests, JSON payloads, filter expressions, or aligner/reducer aggregations for Cloud Monitoring metrics and charts. Don't use for metric discovery or metric selection.OficialPlanificareFără avertismente★ 21,5 K↓ —
- google-cloud-networking-observabilitygoogle/skillsInvestigates Google Cloud networking issues by analyzing GCP logs, metrics, and diagnostics. Use when investigating dropped network traffic, packet drops, drop reasons, VPC Flow Logs (including Private Service Connect / PSC, serverless / App Engine Direct VPC, and cost estimation), NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics. Don't use for generic VM management or non-observability tasks.OficialDevOpsFără avertismente★ 21,5 K↓ —
- google-cloud-slo-alert-configurationgoogle/skillsConfigures Cloud Monitoring PromQL-based Service Level Objective (SLO) alerting policies on Google Cloud for resources registered in App Hub or individually specified. Generates Terraform output. Use when the user asks to configure an SLO or Service Level Objective. Don't use for standard alerting policies.OficialDevOpsFără avertismente★ 21,5 K↓ —
- teachsickn33/agentic-awesome-skillsTeach the user a new skill or concept, within this workspace.AlteleFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- aws-s3sickn33/agentic-awesome-skillsConfigure S3 buckets, policies, and lifecycle rules. Implement versioning, replication, and security. Use when managing object storage on AWS.DevOpsFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- githubsickn33/agentic-awesome-skillsUse the `gh` CLI for issues, pull requests, Actions runs, and GitHub API queries.InginerieFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- hf-cloud-sagemaker-deployment-plannerhuggingface/skillsPlan and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, serve, or expose a model on SageMaker or AWS — including phrases like "deploy a model", "host this LLM on AWS", "serve this embedding model", "deploy a reranker", "deploy a text-to-image / diffusion model", "host this for async inference", "create an endpoint", "serve my fine-tuned model", or any request that involves making a model available for inference on AWS. Use this even when the user is vague (e.g. "I just want to get this running on AWS, you figure it out"). Works for text-generation LLMs, embedding models, rerankers, classifiers, text-to-image / diffusion models — picks the right serving stack and chooses between real-time and async inference. This is the entry-point skill for SageMaker deployment work — it asks clarifying questions, picks a deployment pathway, and coordinates the other deployment skills.OficialDevOpsFără avertismente★ 11,2 K↓ —
- huggingface-besthuggingface/skillsUse when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers on: "best model for X", "what model should I use for", "top models for [task]", "which model runs on my laptop/machine/device", "recommend a model for", "what LLM should I use for", "compare models for", "what's state of the art for", or any question about choosing an AI model for a specific use case. Always use this skill when the user wants model recommendations or comparisons, even if they don't explicitly mention HuggingFace or benchmarks.OficialPlanificareFără avertismente★ 11,2 K↓ —
- hf-memhuggingface/skillsHugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face HubOficialInginerieFără avertismente★ 11,2 K↓ —Apare și în 1 alt depozit
- transformers-jshuggingface/skillsUse Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript. Supports NLP (text classification, translation, summarization), computer vision (image classification, object detection), audio (speech recognition, audio classification), and multimodal tasks. Works in browsers and server-side runtimes (Node.js, Bun, Deno) with WebGPU/WASM using pre-trained models from Hugging Face Hub.OficialMediaFără avertismente★ 11,2 K↓ —Apare și în 1 alt depozit
- huggingface-spaceshuggingface/skillsBuild, deploy, and maintain applications on Hugging Face Spaces — Gradio / Docker / Static SDKs, ZeroGPU and dedicated hardware, model loading, debugging, buckets, inference providers, community grants. Use whenever the user asks to create or host an app on Hugging Face, port code onto ZeroGPU, fix a Space that won't build or run, or otherwise work with `hf spaces …`, `@spaces.GPU`, Space README frontmatter, or the `spaces` Python package.OficialDevOpsFără avertismente★ 11,2 K↓ —
- huggingface-gradiohuggingface/skillsBuild Gradio web UIs and demos in Python. Use when creating or editing Gradio apps, components, event listeners, layouts, or chatbots.OficialRedactareFără avertismente★ 11,2 K↓ —
- huggingface-lora-space-builderhuggingface/skillsBuild and publish a Gradio demo on Hugging Face Spaces for a user-provided LoRA. Use when someone asks to create, generate, ship, or publish a Space, demo, Gradio app, or playground for a LoRA — including LoRAs for Qwen-Image, Qwen-Image-Edit, LTX-Video, Wan, FLUX, SDXL, or other diffusion base models. Also triggers when someone describes a LoRA they trained or hosts on the Hub and wants to share it. Covers picking the right base pipeline and `diffusers` inference recipe, designing a UI tailored to the LoRA's task and inputs (Union/multi-task control, edit, video, image, etc.), respecting model-card recommendations (trigger words, steps, guidance, LoRA scale, example inputs), and shipping to ZeroGPU hardware as a private Space by default.OficialDesignFără avertismente★ 11,2 K↓ —
- huggingface-trackiohuggingface/skillsTrack and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, alerts with webhooks, HF Space syncing, and JSON output for automation.OficialInginerieFără avertismente★ 11,2 K↓ —
- huashu-designalchaincyf/huashu-design花叔Design——用HTML做高保真原型、幻灯片、动画、可视化与专家评审。任何新设计100%先出三个方向初稿给用户选（指定风格/品牌也不豁免），选定后才执行。触发词：做原型、PPT、幻灯片、动画、设计风格、评审、做个HTML页面、UI mockup、导出MP4/GIF、做个好看的。生产级Web App/需后端的系统不适用。DesignFără avertismente★ 26,1 K↓ —Apare și în 1 alt depozit
memory-review
alirezarezvani/claude-skills
InginerieActualizat alaltăieri
De la autor
380 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.
Antetul nu a putut fi citit (no frontmatter); afișăm numele folderului.
Instalare
npx skills add alirezarezvani/claude-skills --skill memory-review -a claude-code
Se instalează în .claude/skills/memory-review/ · 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 94
Securitate100
Proveniență93
Întreținere100
Licență100
Adopție69
Fișiere (1)
- SKILL.md