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-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★ 21,5 K↓ —
- tamarindK-Dense-AI/scientific-agent-skillsProvides access to a collection of open-source molecular design and structural biology tools on the Tamarind Bio platform, via its REST API or MCP server — no local GPUs required. Tamarind bundles popular open-source models for structure prediction (AlphaFold, Boltz, Chai, ESMFold), protein, binder, and de novo design (RFdiffusion, ProteinMPNN, BoltzGen), antibody and nanobody design and developability, protein-ligand docking (DiffDock, Autodock Vina), binding-affinity prediction, MSA generation, and molecular dynamics. Use when the user mentions Tamarind or tamarind.bio, wants to run any of these open-source tools in the cloud, references app.tamarind.bio/api or the x-api-key header, or needs to submit batches of sequences for structural or biophysical characterization.DesignFără avertismente★ 54,4 K↓ —Apare și în 1 alt depozit
- 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
- shortsickn33/agentic-awesome-skillsRewrite the previous response more briefly while preserving the substance.AlteleFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- tmuxsickn33/agentic-awesome-skillsExpert tmux session, window, and pane management for terminal multiplexing, persistent remote workflows, and shell scripting automation.AlteleFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- astrosickn33/agentic-awesome-skillsBuild content-focused websites with Astro — zero JS by default, islands architecture, multi-framework components, and Markdown/MDX support.PlanificareFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- convexsickn33/agentic-awesome-skillsConvex reactive backend expert: schema design, TypeScript functions, real-time subscriptions, auth, file storage, scheduling, and deployment.DevOpsFără 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
- nextflowK-Dense-AI/scientific-agent-skillsBuilds, runs, and debugs Nextflow DSL2 pipelines and nf-core workflows. Use for Nextflow, nf-core, .nf files, nextflow.config, processes/channels/operators, samplesheets, nf-test, modules/subworkflows, container and executor configuration, HPC/SLURM or cloud deployment, and failed or resumed pipeline runs.TestareFără avertismente★ 54,4 K↓ —Apare și în 1 alt depozit
- 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
- dhdna-profilerK-Dense-AI/scientific-agent-skillsApplies the DHDNA framework as an exploratory rubric for reasoning and writing patterns in supplied text. Used for explicit requests for DHDNA, cognitive-style reflection, a thinking-pattern profile, or comparisons of textual reasoning. Scores describe evidence in the sample, not validated psychological traits or personal identity.RedactareFără avertismente★ 54,4 K↓ —
- jobgptsickn33/agentic-awesome-skillsJob search automation, auto apply, resume generation, application tracking, salary intelligence, and recruiter outreach using the JobGPT MCP server.AlteleFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- jqsickn33/agentic-awesome-skillsExpert jq usage for JSON querying, filtering, transformation, and pipeline integration. Practical patterns for real shell workflows.AlteleFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- byagentsickn33/agentic-awesome-skillsPublish agent-written Markdown or HTML as a shareable link with the byagent CLI, then read readers' line comments back, edit, republish to the same link and resolve them.RedactareFără 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↓ —
- 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
- hf-mcphuggingface/skillsUse Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use Gradio Spaces as AI tools. Available when connected to the HF MCP server.OficialAlteleFără avertismente★ 11,2 K↓ —Apare și în 1 alt depozit
- huggingface-datasetshuggingface/skillsUse this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.OficialInginerieFără 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↓ —
- huggingface-zerogpuhuggingface/skillsAI demos and GPU compute with Gradio Spaces and Hugging Face Spaces ZeroGPU. Use when writing or reviewing code that uses `@spaces.GPU`, configuring `python_version` or `requirements.txt` for a ZeroGPU Space, or handling ZeroGPU-specific code constraints — pickle-based process isolation, `gr.State` semantics across the worker boundary, no `torch.compile` (use AoTI instead), CUDA wheel-only builds (no `nvcc` at build or runtime), large vs xlarge sizing, and dynamic duration callables. Make sure to use this skill whenever the user mentions ZeroGPU, `@spaces.GPU`, or the `spaces` Python package, or hits ZeroGPU-specific code errors like `PicklingError` across the worker boundary, `illegal duration`, or `flash-attn` wheel-build failures — even when the user does not explicitly ask for ZeroGPU coding guidance. Trigger on `import spaces` or `@spaces.GPU` in code.OficialRedactareFără 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
- huggingface-papershuggingface/skillsLook up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.OficialȘtiințăFără avertismente★ 11,2 K↓ —
nx-workspace-patterns
wshobson/agents
AlteleActualizat ieri
De la autor
Configure and optimize Nx monorepo workspaces. Use when setting up Nx, configuring project boundaries, optimizing build caching, or implementing affected commands.
Instalare
npx skills add wshobson/agents --skill nx-workspace-patterns -a claude-code
Se instalează în .claude/skills/nx-workspace-patterns/ · 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 (2)
- SKILL.md
- references/details.md