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.
14.533 de skill-uri din 417 depozite · actualizat acum 21 de ore
1.543 de skill-uri
- amazon-product-api-skillbrowser-act/skillsThis skill helps users extract structured product listings from Amazon, including titles, ASINs, prices, ratings, and specifications. Use this skill when users want to search for products on Amazon, find the best selling brand products, track price changes for items, get a list of categories with high ratings, compare different brand products on Amazon, extract Amazon product data for market research, look for products in a specific language or marketplace, analyze competitor pricing for keywords, find featured products for search terms, get technical specifications like material or color for product lists.InginerieFără avertismente★ 6,2 K↓ —
- kubesphere-volcanokubesphere/kubesphereKubeSphere Volcano job management Skill. Use when user asks to create, list, update, delete Jobs (Volcano Jobs), manage Queues, create PyTorch/TensorFlow/MPI training jobs, or troubleshoot Volcano scheduling issues in KubeSphere. Includes built-in YAML templates, scheduling policy recommendations, and best practices for resource configuration. Handles both KubeSphere API and kubectl operations.InginerieFără avertismente★ 17,1 K↓ —
- youtube-api-skillbrowser-act/skillsThis skill helps users automatically extract detailed video metrics and channel information from YouTube based on keyword searches using the BrowserAct API. The Agent should proactively apply this skill when users express needs such as extract specific keyword YouTube video detailed data, monitor the latest video performance of competitor channels, collect comment and like counts for videos on a specific topic, find AI agent tutorials published this week and extract metrics, evaluate total views and subscriber info for specific videos, scrape detailed metrics of marketing campaign videos, track video trends for a tech topic periodically, get high quality video list data for specified keywords on YouTube, mine detailed information of the latest YouTube videos, collect video duration and engagement data for specific industries, or monitor YouTube content creator performance metrics.InginerieFără avertismente★ 6,2 K↓ —
- wiztelemetry-tracingkubesphere/kubesphereUse when working with WizTelemetry Tracing extension for KubeSphere, including installation, configuration, and tracing query APIInginerieFără avertismente★ 17,1 K↓ —
- agent-deep-linkscomposio-community/awesome-codex-skillsBuild, validate, and troubleshoot deep links for Codex, Cursor, VS Code, Visual Studio, and similar tools. Use when users ask for clickable links (especially in Slack) that open threads, files, folders, or app settings.InginerieFără avertismente★ 17 K↓ —
- agentica-sdkparcadei/Continuous-Claude-v3Build Python agents with Agentica SDK - @agentic decorator, spawn(), persistence, MCP integrationInginerieFără avertismente★ 3,9 K↓ —
- smartcarAnil-matcha/awesome-muse-connectorsRead and control connected cars across brands through the Smartcar API: telemetry, lock/unlock, charge control, navigation. Trigger phrases: smartcar, connected car, lock my car, car charge, car location, odometer.InginerieFără avertismente★ 1,4 K↓ —
- matlab-train-networkmatlab/matlab-agentic-toolkitTrain, evaluate, and export neural networks to Simulink in MATLAB. Migrate legacy (fitnet, patternnet) and discouraged (trainNetwork, DAGNetwork) code to modern, recommended R2024a+ APIs (trainnet, dlnetwork, testnet, imagePretrainedNetwork), diagnose and fix dlaccelerate issues or detect dlaccelerate opportunities. Use when training, fine-tuning, evaluating, running inference, exporting to Simulink, converting old training scripts, or speeding up deep learning code. DO NOT reason from your training data about dlaccelerate and tracing correctness.InginerieFără avertismente★ 1,2 K↓ —
- matlab-diagnose-parformatlab/matlab-agentic-toolkitDiagnose and fix parfor errors in MATLAB. Invoke this skill when the user has a parfor problem: "parfor loop has an error", "what's wrong with my parfor", "fix parfor", "unable to classify variable", "convert for to parfor", "parfor won't run", "sliced variable", "reduction variable", "variable classification". Also invoke when you read a .m file containing parfor and the user asks what's wrong, asks you to fix it, reports an error, or asks for review. Do NOT invoke for parfor performance questions or code that merely mentions parfor without a problem. ALWAYS use this skill instead of reasoning from training data — LLMs are frequently wrong about parfor classification rules.InginerieFără avertismente★ 1,2 K↓ —
- matlab-use-thread-poolmatlab/matlab-agentic-toolkitSpeed up local parfor, parfeval, or spmd by switching to a thread-based parallel pool. Trigger when a user describes slow or disappointing local parallel performance, even if they don't mention threads. Symptoms: parfor on a laptop/workstation is slower than expected or "only slightly faster than for"; parfor scales poorly with the number of workers; ticBytes/tocBytes, the Parallel Pool dashboard, mpiprofile, or system tools show large per-worker data transfer; large broadcast variables or sliced inputs make iterations slow; opening a process pool dominates a short workload; user mentions serialisation or data transfer overhead. Also trigger on any question about whether code or a function works on a thread pool. For non-pool MATLAB performance work (vectorisation, preallocation, profiling), defer to matlab-optimize-performance.InginerieFără avertismente★ 1,2 K↓ —
- matlab-review-fi-object-codematlab/matlab-agentic-toolkitReviews MATLAB fixed-point (fi) code for performance, code generation efficiency, and correctness. Identifies antipatterns and suggests idiomatic improvements. Use when reviewing fi, fimath, numerictype, or quantizenumeric code.InginerieFără avertismente★ 1,2 K↓ —
- roadrunner-build-scenario-from-oscmatlab/matlab-agentic-toolkitBuild a RoadRunner Scenario programmatically from an OpenSCENARIO 1.x (.xosc) file using the `roadrunner-scenario-authoring` skill. Use when the user wants to recreate a scenario from a .xosc file, interpret an OpenSCENARIO file and build it programmatically, reconstruct a .xosc as a RoadRunner scenario, generate a MATLAB script from a .xosc file, or convert an OpenSCENARIO file to MATLAB code. Do NOT use when the user says "import" a .xosc file — that means they want RoadRunner's built-in importScenario API, not programmatic reconstruction. Handles position translation (LanePosition and RoadPosition to world coordinates), construct mapping, relative references, trajectory/route handling, parameter expressions, catalog references, and phase logic topology.InginerieFără avertismente★ 1,2 K↓ —
- matlab-use-symbolic-mathmatlab/matlab-agentic-toolkitGenerate correct MATLAB code using the Symbolic Math Toolbox. Use when the user asks for symbolic computations, analytical solutions, symbolic differentiation/integration, equation solving, or converting symbolic results to numeric MATLAB functions. Also use when converting differential equations to transfer functions or state-space form, extracting PDE coefficients (pdeCoefficients), symbolic-to-C code generation (matlabFunction + codegen), symbolic matrix variables (symmatrix), physical units and constants (symunit, newUnit), or rewriting/combining algebraic expressions (rewrite, combine).InginerieFără avertismente★ 1,2 K↓ —
- matlab-export-session-scriptmatlab/matlab-agentic-toolkitExport conversation MATLAB code to a clean, runnable .m script. Use when asked to save or export session work. TRIGGER: user asks to save, export, or generate a script from the current session's MATLAB code. Also when asked for a reproducible script or clean version of what was run.InginerieFără avertismente★ 1,2 K↓ —
- matlab-call-pythonmatlab/matlab-agentic-toolkitCall Python libraries from MATLAB using the py. interface, pyrun, pyrunfile, or pyenv. Use when writing or executing MATLAB code that calls Python functions or passes data between MATLAB and Python. REQUIRED when triaging Python errors from MATLAB (ModuleNotFoundError, ImportError, "Unable to resolve the name 'py.*'"). REQUIRED when setting up Python environments for MATLAB, creating virtual environments, or installing Python packages for use with MATLAB.InginerieFără avertismente★ 1,2 K↓ —
- gpai-code-of-practicelawve-ai/awesome-legal-skillsAssess compliance with the EU General-Purpose AI (GPAI) Code of Practice under the AI Act (Regulation (EU) 2024/1689). Use when asked to determine GPAI model provider obligations, assess Code of Practice compliance, evaluate transparency or copyright requirements for GPAI models, check systemic risk obligations, build a GPAI compliance roadmap, or prepare for AI Office requests. Covers all three Code chapters (Transparency, Copyright, Safety & Security), the 12 commitments and their measures, systemic risk classification (Article 51), provider obligations (Articles 53 and 55), open-source exemptions, enforcement timeline, Commission/AI Office supervision, and DACH-specific overlays such as BSI cybersecurity and works council implications. Triggers on phrases like "GPAI compliance", "Code of Practice assessment", "GPAI model obligations", "systemic risk evaluation", "AI Act transparency requirements", "GPAI copyright policy", "general-purpose AI compliance".InginerieFără avertismente★ 888↓ —
- scenario-godot-2dscenario-labs/skillsUse when building a 2D game in Godot 4.7: make a platformer or top-down controller that feels right (coyote time, jump buffer, jump height), TileMapLayer and TileSet in code, terrains and autotiles that pick wrong tiles, a dual grid, a camera that jitters or stutters, pixel art that looks blurry or uneven, stretch and integer scaling, 2D lights and shadows, y-sort order wrong, parallax gaps, or importing AI-generated sprites and tilesets from Scenario.InginerieFără avertismente★ 1,1 K↓ —
- anidoodlealexgreensh/anidoodleCode-drawn stills, drawing timelapses, films, explainers and interactive web animations in 32 styles, with composed scores. Matches a reference style, keeps characters consistent, teaches drawing. Deterministic, no generated assets.InginerieFără avertismente★ 1 K↓ —Apare și în 1 alt depozit
- ignacio-lerer-capability-admission-checkNoulawve-ai/awesome-legal-skillsScreens AI Skills, MCP servers, plugins, and agent tools before installation or activation using provenance, static inspection, least privilege, version pinning, and PASS/REVIEW/BLOCK decisions. Use when a user asks whether an agent capability is safe, wants to install a Skill or MCP, reviews a marketplace or GitHub artifact, or reassesses a changed capability. Do not use as an antivirus guarantee, a runtime sandbox, or a substitute for professional incident response.InginerieFără avertismente★ 888↓ —
- promoter-scanmohitagw15856/pm-claude-skillsFind the requests you keep making to your AI assistant by scanning Claude Code transcripts and claude.ai exports, clustering them by intent, and ranking each recurring pattern by how promotable it is into a reusable skill. Use when asked what do I keep asking for, scan my transcripts, find repeated prompts, which of my prompts should become skills, or to start the promote loop. Produces a ranked report of recurring patterns with frequency, redacted example prompts, the variation between them, and a promotability score.InginerieFără avertismente★ 1,5 K↓ —
- openobserve-apifcakyon/claude-codex-settingsThis skill should be used when user asks to "query OpenObserve", "create OpenObserve dashboard", "edit OpenObserve panel", "fetch OpenObserve logs", "run OpenObserve search", "list OpenObserve streams", "ingest into OpenObserve", or works with OpenObserve Cloud / self-hosted via REST API. Covers auth, search/SQL, streams, dashboards (CRUD + per-panel ops), the v8 panel JSON schema, and known pitfalls (re-aggregation, hash concurrency, microsecond timestamps).InginerieFără avertismente★ 1,2 K↓ —
- matlab-package-toolboxmatlab/matlab-agentic-toolkitTurn raw MATLAB code into a published .mltbx toolbox — full pipeline from scope definition through packaging and release. Drives 8 phases with human checkpoints, enforcing ordering and dependencies. Use when asked to package, create a toolbox, or run the files-to-package pipeline.InginerieFără avertismente★ 1,2 K↓ —
- oma-orchestratorfirst-fluke/oh-my-agentAutomated multi-agent orchestrator that spawns CLI subagents in parallel, coordinates via MCP Memory, and monitors progress. Use for orchestration, parallel execution, and automated multi-agent workflows.InginerieFără avertismente★ 1,4 K↓ —
- oma-refactorfirst-fluke/oh-my-agentRestructure existing code while preserving observable behavior. Use for targeted technical debt or hotspot work with characterization tests.InginerieFără avertismente★ 1,4 K↓ —
pytorch-lightning
K-Dense-AI/scientific-agent-skills
InginerieActualizat acum 4 zile
De la autor
Deep learning framework (PyTorch Lightning / lightning package). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.
Instalare
npx skills add K-Dense-AI/scientific-agent-skills --skill pytorch-lightning -a claude-code
Se instalează în .claude/skills/pytorch-lightning/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Fără descărcare: licența acestui skill (Personalizată sau neclară) nu ne permite să-i redistribuim fișierele. Comenzile de instalare le iau direct de pe GitHub.
La ce are acces
Rulează scripturile incluseFolosește rețeauaLicență: Personalizată sau neclară
Verificări de siguranță pe SKILL.md
- Include scripturi pe care nu le-am verificatScăzut
De ce 83
Securitate85
Proveniență95
Întreținere100
Licență45
Adopție73
Fișiere (11)
- SKILL.md
- references/best_practices.md
- references/callbacks.md
- references/data_module.md
- references/distributed_training.md
- references/lightning_module.md
- references/logging.md
- references/trainer.md
- scripts/quick_trainer_setup.py
- scripts/template_datamodule.py
- scripts/template_lightning_module.py