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.
44.168 de skill-uri din 2.108 depozite · actualizat acum 4 minute
44.168 de skill-uri
- training-llms-megatronOrchestra-Research/AI-Research-SKILLsTrains large language models (2B-462B parameters) using NVIDIA Megatron-Core with advanced parallelism strategies. Use when training models >1B parameters, need maximum GPU efficiency (47% MFU on H100), or require tensor/pipeline/sequence/context/expert parallelism. Production-ready framework used for Nemotron, LLaMA, DeepSeek.ProductivitateFără avertismente★ 13,9 K↓ —
- pytorch-fsdp2Orchestra-Research/AI-Research-SKILLsAdds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with DeviceMesh.ProductivitateFără avertismente★ 13,9 K↓ —
- cost-optimizationmicrosoft/skillsOptimize existing Azure resources and analyze Reservations or Savings Plans. WHEN: "optimize Azure costs", "reduce cloud spending", "rightsize resources", "find idle resources", "orphaned disk", "deleted VM still charged", "public IP still charging", "reservation utilization", "Savings Plan coverage", "commitment recommendation", "why is pay-as-you-go still charged". DO NOT USE FOR: cost spikes, forecasts, pricing estimates, budgets, or governance.OficialDevOpsFără avertismente★ 3,1 K↓ —Apare și în 1 alt depozit
- distributed-llm-pretraining-torchtitanOrchestra-Research/AI-Research-SKILLsProvides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). Use when pretraining Llama 3.1, DeepSeek V3, or custom models at scale from 8 to 512+ GPUs with Float8, torch.compile, and distributed checkpointing.AlteleFără avertismente★ 13,9 K↓ —
- kqlmicrosoft/skillsKQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and advanced functions (geo, vector, graph). USE THIS SKILL whenever writing, debugging, or reviewing KQL queries — even simple ones — because the gotchas section prevents the most common errors that waste tool calls and cause expensive retry cascades. Trigger on: KQL, Kusto, ADX, Azure Data Explorer, Fabric Real-Time Intelligence, EventHouse, Log Analytics, log analysis, data exploration, time series, anomaly detection, summarize, where clause, join, extend, project, let statement, parse operator, extract function, any mention of pipe-forward query syntax.OficialDevOpsFără avertismente★ 3,1 K↓ —
- agent-platform-migrate-from-ai-studiogoogle/skillsGuides agents and users through migrating from Gemini API in Google AI Studio to Gemini Enterprise Agent Platform (formerly Vertex AI). Use this skill when moving applications to Google Cloud, to leverage Cloud credits, or to unify inferencing with other Cloud infrastructure (IAM, billing, telemetry).OficialDevOpsFără avertismente★ 21,5 K↓ —
- result-to-claimwanshuiyin/Auto-claude-code-research-in-sleepUse when experiments complete to judge what claims the results support, what they don't, and what evidence is still missing. Codex MCP evaluates results against intended claims and routes to next action (pivot, supplement, or confirm). Use after experiments finish — before writing the paper or running ablations.ȘtiințăFără avertismente★ 18 K↓ —
- meta-applywanshuiyin/Auto-claude-code-research-in-sleepPrivileged applier that LANDS meta-optimize / corpus-audit patches the user approved — the ONLY skill permitted to mutate the skill corpus from a self-modification proposal, with cross-model jury and human approval at landing. Use when the user says "meta apply", "/meta-apply", "land the staged patches", "应用优化", after a /meta-optimize run.AlteleFără avertismente★ 18 K↓ —
- modal-serverless-gpuOrchestra-Research/AI-Research-SKILLsServerless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.DevOpsFără avertismente★ 13,9 K↓ —
- azure-kusto-irql-graphmicrosoft/skillsApply IRQL graph functions to KQL or IRQL query results for Kusto Explorer visualization. Generates Lift_To_Graph mappings and composes Graph_Render_View, Graph_Fold_By_Property, Extract_Node_*, Enrich_Node_*, and Enrich_Graph_* calls. Accepts a supplied query or limited basic natural-language source request; it is not a general natural-language-to-KQL/IRQL skill. WHEN: Lift_To_Graph, Graph_Render_View, Graph_Fold_By_Property, IRQL graph enrichment, graph mapping for existing query results, icon-decorated graph, fold graph nodes. Use azure-kusto-graph for native make-graph analysis, graph-match, shortest paths, components, or persistent graphs.OficialDevOpsFără avertismente★ 3,1 K↓ —Apare și în 1 alt depozit
- azure-kubernetesmicrosoft/skillsPlan, create, and configure production-ready Azure Kubernetes Service (AKS) clusters. Covers Day-0 checklist, SKU selection (Automatic vs Standard), networking options (private API server, Azure CNI Overlay, egress configuration), security, and operations (autoscaling, upgrade strategy, cost analysis). WHEN: create AKS environment, provision AKS, enable AKS observability, design AKS networking, choose AKS SKU, secure AKS, optimize AKS, AKS spot nodes, AKS cluster-autoscaler, rightsize AKS pod, pod rightsizing, over-provisioned AKS pod, pod resource requests and limits, Vertical Pod Autoscaler, VPA recommendations.OficialDevOpsFără avertismente★ 3,1 K↓ —Apare și în 2 alte depozite
- azure-kusto-irqlmicrosoft/skillsCompose IRQL (Incident Response Query Language) queries for Kusto cybersecurity investigations. Translates natural language hunting questions into composable IRQL pipelines using Get_*, Extract_*, and Enrich_* functions. WHEN: IRQL query, security hunt, threat hunting KQL, incident response query, compose hunting pipeline, failed logins, phishing investigation, lateral movement, process execution, file creation events.OficialDevOpsFără avertismente★ 3,1 K↓ —Apare și în 1 alt depozit
- azure-messagingmicrosoft/skillsTroubleshoot and resolve issues with Azure Messaging SDKs for Event Hubs and Service Bus. Covers connection failures, authentication errors, message processing issues, and SDK configuration problems. WHEN: event hub SDK error, service bus SDK issue, messaging connection failure, AMQP error, event processor host issue, message lock lost, message lock expired, lock renewal, lock renewal batch, send timeout, receiver disconnected, SDK troubleshooting, azure messaging SDK, event hub consumer, service bus queue issue, topic subscription error, enable logging event hub, service bus logging, eventhub python, servicebus java, eventhub javascript, servicebus dotnet, event hub checkpoint, event hub not receiving messages, service bus dead letter, batch processing lock, session lock expired, idle timeout, connection inactive, link detach, slow reconnect, session error, duplicate events, offset reset, receive batch.OficialDevOpsFără avertismente★ 3,1 K↓ —Apare și în 2 alte depozite
- metronomestripe/aiGuides Metronome usage-based billing integration decisions — event ingestion (single and batch, idempotency, billable metrics), contract design (rate cards, overrides, dimensional pricing, products), invoicing lifecycle (grace periods, finalization, Stripe sync), credit and commit management (prepaid, postpaid, thresholds, auto-recharge), and Stripe integration (arrears invoicing, tax providers, line item limits). Use when building, modifying, or reviewing any Metronome integration — including ingesting usage events, creating customers, contracts, or rate cards, designing billable metric group keys, managing credits and commits, configuring invoicing, syncing invoices with Stripe Billing, billing AI applications for token usage, setting up self-serve (PLG) pricing, reviewing customer health, commit burn, portfolios, or renewals, or migrating from Stripe Billing Meters to Metronome.OficialDesignFără avertismente★ 2 K↓ —Apare și în 4 alte depozite
- entra-agent-idmicrosoft/skillsProvision Microsoft Entra Agent Identity Blueprints, BlueprintPrincipals, and per-instance Agent Identities via Microsoft Graph, and configure OAuth 2.0 token exchange (fmi_path, OBO, cross-tenant) including the Microsoft Entra SDK for AgentID sidecar. USE FOR: Agent Identity Blueprint, BlueprintPrincipal, agent OAuth, fmi_path token exchange, agent OBO, Workload Identity Federation for agents, polyglot agent auth, Microsoft.Identity.Web.AgentIdentities. DO NOT USE FOR: standard Entra app registration (use entra-app-registration), Microsoft Foundry agent authoring (use microsoft-foundry).OficialAlteleFără avertismente★ 3,1 K↓ —Apare și în 2 alte depozite
- basincloudflare/skillsBuild and troubleshoot Cloudflare Basin analytics workflows with Basin Pipelines, Basin Catalog, and Basin SQL. Use for streaming data into R2 Iceberg tables, managing catalogs, or querying those tables; also use for requests using the former Data Platform, Pipelines, R2 Data Catalog, or R2 SQL names.OficialDevOpsFără avertismente★ 3,2 K↓ —Apare și în 1 alt depozit
- ray-dataOrchestra-Research/AI-Research-SKILLsScalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.DateFără avertismente★ 13,9 K↓ —Apare și în 1 alt depozit
- skypilot-multi-cloud-orchestrationOrchestra-Research/AI-Research-SKILLsMulti-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.AlteleFără avertismente★ 13,9 K↓ —Apare și în 2 alte depozite
- huggingface-accelerateOrchestra-Research/AI-Research-SKILLsSimplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). Interactive config, single launch command. HuggingFace ecosystem standard.InginerieFără avertismente★ 13,9 K↓ —Apare și în 1 alt depozit
- unslothOrchestra-Research/AI-Research-SKILLsExpert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimizationProductivitateFără avertismente★ 13,9 K↓ —Apare și în 2 alte depozite
- azure-computemicrosoft/skillsAzure VM/VMSS router. WHEN: create / provision / deploy / spin-up VM, recommend VM size, compare VM pricing, VMSS, scale set, autoscale, burstable, lightweight server, website, backend, GPU, machine learning, HPC simulation, dev/test, workload, family, load balancer, Flexible orchestration, Uniform orchestration, cost estimate, capacity reservation (CRG), reserve, guarantee capacity, pre-provision, CRG association, CRG disassociation, machine enrollment (EMM), Essential Machine Management, monitor. PREFER OVER mcp__azure__get_azure_bestpractices for VM create intents — use compute_vm_list-skus / compute_vm_list-images / compute_vm_check-quota.OficialDevOpsFără avertismente★ 3,1 K↓ —Apare și în 2 alte depozite
- stripe-appsstripe/aiBuild, modify, or review Stripe Apps and extensions using the relevant documentation and reference guides. Use for custom Stripe Dashboard UI, stripe-app.yaml, @stripe/ui-extension-sdk, @stripe/extensibility-sdk, script extensions, extension interfaces, custom workflow actions, and apps that authenticate to Stripe or react to events. Also use when deciding whether a Stripe extension can support the user's billing or workflow requirements.OficialDesignFără avertismente★ 2 K↓ —Apare și în 4 alte depozite
- firebase-firestorefirebase/agent-skillsSets up, manages, queries, and configures Cloud Firestore databases (Standard/Enterprise edition), including data modeling, security rules, indexes, and SDK integrations (Web, Python, iOS, Android, Flutter). Use when creating/listing Firestore databases, defining data models/indexes, writing SDK queries, or integrating Firestore SDKs. For authoring or modifying Firestore Security Rules (firestore.rules), delegate to the firestore-rules-author subagent if subagent delegation is available, or use firestore-rules-creation otherwise. Don't use for Firebase Hosting, Data Connect, Auth, Storage/GCS, Crashlytics, Functions, or BigQuery.OficialSecuritateFără avertismente★ 484↓ —
- firebase-app-hosting-basicsfirebase/agent-skillsDeploys and manages full-stack web applications (Next.js, Angular) with Server-Side Rendering (SSR) using Firebase App Hosting. Use when deploying Next.js/Angular apps, configuring apphosting.yaml or firebase.json apphosting blocks, managing secrets, setting up GitHub CI/CD, or configuring Blaze billing requirements. Don't use for classic static web hosting, Auth, Firestore, Crashlytics, or Xcode.OficialDevOpsFără avertismente★ 484↓ —
flutter-implement-json-serialization
flutter/agent-plugins
OficialAlteleActualizat acum 4 zile
De la autor
Create model classes with `fromJson` and `toJson` methods using `dart:convert`. Use when manually mapping JSON keys to class properties for simple data structures.
Instalare
npx skills add flutter/agent-plugins --skill flutter-implement-json-serialization -a claude-code
Se instalează în .claude/skills/flutter-implement-json-serialization/ · 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: BSD-3-CLAUSE
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De ce 93
Securitate100
Proveniență100
Întreținere100
Licență100
Adopție56
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- SKILL.md