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.
45.100 de skill-uri din 2.196 de depozite · actualizat acum 8 ore
45.098 de skill-uri
- presentation-stylingshanraisshan/claude-code-best-practiceKnowledge about CSS classes, component patterns, and syntax highlighting in the presentationDesignFără avertismente★ 68,1 K↓ —
- before-you-buildwshobson/agentsPre-build product and feature risk review for founders, product managers, and AI-assisted builders. Use this skill when the user is about to build a landing page, MVP, SaaS product, internal tool, agent workflow, or major feature and needs to check demand, positioning, monetization, retention, trust, distribution, and adoption risk before implementation starts.DesignFără avertismente★ 41,7 K↓ —
- gen-specs-as-issuesgithub/awesome-copilotThis workflow guides you through a systematic approach to identify missing features, prioritize them, and create detailed specifications for implementation.PlanificareFără avertismente★ 40,4 K↓ —
- inngestsickn33/agentic-awesome-skillsInngest expert for serverless-first background jobs, event-driven workflows, and durable execution without managing queues or workers.AlteleFără avertismente★ 48,5 K↓ —
- create-specificationgithub/awesome-copilotCreate a new specification file for the solution, optimized for Generative AI consumption.PlanificareFără avertismente★ 40,4 K↓ —
- lora-qlora-recipeswshobson/agentsConfigure LoRA and QLoRA supervised fine-tuning with current best-practice hyperparameters. Use when writing or reviewing a LoRA/QLoRA training configuration, choosing rank/alpha/target modules, or deciding between LoRA, QLoRA, and full fine-tuning.RedactareFără avertismente★ 41,7 K↓ —
- jev-usesickn33/agentic-awesome-skillsRoute enumerable judgment steps - did it work, which option, how risky, is this safe to run - to the Jev judgment model through the jev_judge and jev_gate MCP tools, batched into one call per state.AlteleFără avertismente★ 48,5 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↓ —
- gke-batch-hpcgoogle/skillsRuns batch and HPC workloads on GKE, utilizing job queues and parallel processing. Use when running GKE batch jobs, configuring GKE HPC, or setting up GKE job queues. Don't use for standard web application deployments (use gke-app-onboarding instead).OficialDevOpsFără avertismente★ 21,6 K↓ —
- llm-evaluationwshobson/agentsImplement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.TestareFără avertismente★ 41,7 K↓ —
- aws-cdk-python-setupgithub/awesome-copilotSetup and initialization guide for developing AWS CDK (Cloud Development Kit) applications in Python. This skill enables users to configure environment prerequisites, create new CDK projects, manage dependencies, and deploy to AWS.DevOpsFără avertismente★ 40,4 K↓ —
- google-cloud-storage-bucket-architectgoogle/skillsCreates Cloud Storage on Google Cloud (also known colloquially as GCS) buckets. Analyzes the workload (sensitive data, media hosting, ingestion, web hosting, archiving, backup, logging, analytics, AI/ML, or general-purpose), validates project-level security settings, and designs a secure-by-default, cost-effective configuration (location, storage class, uniform bucket-level access, public access prevention, soft delete, lifecycle) before creating it. Use whenever a user wants to create, make, set up, provision, or spin up a bucket, or needs object storage for an app, service, pipeline, or dataset — even a "simple" or "default" bucket, or when bucket creation is one step in a larger workflow. Outputs or executes the creation via gcloud, the JSON/REST API, Terraform, or SDK client libraries (C++, Java, Python, Go). Don't use for anything other than creating new buckets — for uploads, downloads, access changes, or reconfiguring existing buckets, use google-cloud-storage-basics.OficialPlanificareFără avertismente★ 21,6 K↓ —
- prdgithub/awesome-copilotGenerate high-quality Product Requirements Documents (PRDs) for software systems and AI-powered features. Includes executive summaries, user stories, technical specifications, and risk analysis.PlanificareFără avertismente★ 40,4 K↓ —Apare și în 2 alte depozite
- brand-landingpagewshobson/agentsBrand-first landing page designer — runs a brand-identity interview (colors, typography, shape language), then generates and iterates on a polished landing page via Stitch with deployment-ready HTML. Use when the user asks to create, design, or build a landing page, homepage, or marketing page and has no established visual direction. Skip when they have a design mockup, need a dashboard or app UI, are working at component level, building a multi-page app, or restyling with known design tokens — use frontend-design instead.DevOpsFără avertismente★ 41,7 K↓ —
- gcp-gkesickn33/agentic-awesome-skillsDeploy and manage Google Kubernetes Engine clusters. Configure node pools, networking, and workload identity. Use when running Kubernetes on GCP.DevOpsFără avertismente★ 48,5 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↓ —
- falsifysickn33/agentic-awesome-skillsThe scientific thinking protocol for AI agents. Use when facing complex, ambiguous, or high-stakes questions where guessing is costly: hypothesis → attempt to break it → evidence → calibrated conclusion.ȘtiințăFără avertismente★ 48,5 K↓ —
- python-packagingwshobson/agentsCreate distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to PyPI. Use when packaging Python libraries, creating CLI tools, or distributing Python code.InginerieFără avertismente★ 41,7 K↓ —
- deepapisickn33/agentic-awesome-skillsUse DeepAPI for supported scraping, research, and email workflows with explicit credentials and approval.BrowserFără avertismente★ 48,5 K↓ —
- yes-mdsickn33/agentic-awesome-skills6-layer AI governance: safety gates, evidence-based debugging, anti-slack detection, and machine-enforced hooks. Makes AI safe, thorough, and honest.InginerieFără avertismente★ 48,5 K↓ —
- vizcomsickn33/agentic-awesome-skillsAI-powered product design tool for transforming sketches into full-fidelity 3D renders.DesignFără avertismente★ 48,5 K↓ —
- to-prdsickn33/agentic-awesome-skillsTurn the current conversation into a PRD and publish it to the project issue tracker — no interview, just synthesis of what you've already discussed.PlanificareFără avertismente★ 48,5 K↓ —Apare și în 1 alt depozit
- unslopsickn33/agentic-awesome-skillsPost-process AI-generated text through the unslop CLI to strip AI writing patterns before publishingRedactareFără avertismente★ 48,5 K↓ —
- agent-governancegithub/awesome-copilotPatterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)AlteleFără avertismente★ 40,4 K↓ —
fluentui-blazor
github/awesome-copilot
DesignActualizat acum 22 de ore
De la autor
Guide for using the Microsoft Fluent UI Blazor component library (Microsoft.FluentUI.AspNetCore.Components NuGet package) in Blazor applications. Use this when the user is building a Blazor app with Fluent UI components, setting up the library, using FluentUI components like FluentButton, FluentDataGrid, FluentDialog, FluentToast, FluentNavMenu, FluentTextField, FluentSelect, FluentAutocomplete, FluentDesignTheme, or any component prefixed with "Fluent". Also use when troubleshooting missing providers, JS interop issues, or theming.
Instalare
npx skills add github/awesome-copilot --skill fluentui-blazor -a claude-code
Se instalează în .claude/skills/fluentui-blazor/ · 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
Adopție71
Fișiere (5)
- SKILL.md
- references/DATAGRID.md
- references/LAYOUT-AND-NAVIGATION.md
- references/SETUP.md
- references/THEMING.md