3.3천건 · 관련도순
Access AlphaFold DB's 200M+ predicted structures by UniProt ID. Download PDB/mmCIF, analyze pLDDT/PAE, bulk-fetch proteomes via Google Cloud. For experimental structures use PDB; for prediction use ColabFold or ESMFold.
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Microsoft docs lookup, code samples, and SDK reference for Azure, .NET, Microsoft 365, Windows, and Power Platform via Microsoft Learn MCP. Use for API reference or official MS documentation retrieval.
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Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, model selection/leaderboards and model persistence. Use for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
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Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.
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Azure deployment for web apps — Static Web Apps, App Service, Blob Storage, Bicep/ARM, GitHub Actions CI/CD. Use when deploying Next.js/Vite to Azure or configuring Azure resources for full-stack apps.
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DevOps & Infrastructure IA — Gère le VPS, Docker, déploiements, monitoring, sécurité, tunnels Cloudflare. Expert Hetzner + Coolify + self-hosting.
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GPU monitoring with risk intelligence. Local + cloud fleet monitoring, health tracking, proactive alerts, and AI-powered fleet analytics.
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Use when implementing, integrating, upgrading, debugging, or answering anything involving third-party APIs, libraries, frameworks, CLIs, cloud services, model or provider SDKs, fast-moving product behavior, unfamiliar repo docs or specs, errors that may indicate API drift, or high-stakes auth, security, billing, data, migration, deployment, compliance, or privacy behavior. Forces a docs pass before coding from memory.
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Create polished, validated architecture, workflow, sequence, data-flow, and lifecycle/state diagrams as explorable standalone HTML with inline SVG, dark/light themes, optional trace motion, and PNG/JPEG/WebP/SVG/WebM export. Accept plain-language requirements or pasted Mermaid flowchart, sequenceDiagram, and stateDiagram input; inspect repository evidence when the diagram must reflect real code. Use when the user asks to visualize system architecture, infrastructure, cloud/security/network topology, technical workflows, API call sequences, request lifecycles, data pipelines, ETL/ELT, data lineage, state machines, or to convert/beautify Mermaid.
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Expert guidance for designing, implementing, migrating, and debugging SwiftData persistence in Swift and SwiftUI apps. Use when working with @Model schemas, @Relationship/@Attribute rules, Query or FetchDescriptor data access, ModelContainer/ModelContext configuration, CloudKit sync, SchemaMigrationPlan/history APIs, ModelActor concurrency isolation, or Core Data to SwiftData adoption/coexistence.
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Implement, review, or improve data persistence using SwiftData. Use when defining @Model classes with @Attribute, @Relationship, @Transient, @Unique, or @Index; when querying with @Query, #Predicate, FetchDescriptor, or SortDescriptor; when configuring ModelContainer and ModelContext for SwiftUI or background work with @ModelActor; when planning schema migrations with VersionedSchema and SchemaMigrationPlan; when setting up CloudKit sync with ModelConfiguration; or when coexisting with or migrating from Core Data.
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Provide universal memory capabilities for different AI agents and development frameworks, unifying the capture, retrieval, and management of user, project, and task context.
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This skill should be used when the user asks to "perform vulnerability scanning", "scan networks for open ports", "assess web application security", "scan wireless networks", "detect malware", "check cloud security", or "evaluate system compliance". It provides comprehensive guidance on security scanning tools and methodologies.
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Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.
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This skill should be used when the user asks to "pentest AWS", "test AWS security", "enumerate IAM", "exploit cloud infrastructure", "AWS privilege escalation", "S3 bucket testing", "metadata SSRF", "Lambda exploitation", or needs guidance on Amazon Web Services security assessment.
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Run Playwright tests at scale with cloud-hosted browsers and integrated Azure portal reporting.
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Azure Storage File Share SDK for Python. Use for SMB file shares, directories, and file operations in the cloud.
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Azure Event Grid SDK for Python. Use for publishing events, handling CloudEvents, and event-driven architectures.
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Azure Event Grid SDK for .NET. Client library for publishing and consuming events with Azure Event Grid. Use for event-driven architectures, pub/sub messaging, CloudEvents, and EventGridEvents.
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Provide comprehensive techniques for penetration testing AWS cloud environments. Covers IAM enumeration, privilege escalation, SSRF to metadata endpoint, S3 bucket exploitation, Lambda code extraction, and persistence techniques for red team operations.
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AWS development with infrastructure automation and cloud architecture patterns
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Securing container registry images by implementing vulnerability scanning with Trivy and Grype, enforcing image signing with Cosign and Sigstore, configuring registry access controls, and building CI/CD pipelines that prevent Dağıt:ing unscanned or unsigned images.
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Securing API Gateway endpoints with AWS WAF by configuring managed rule groups for OWASP Top 10 protection, creating custom rate limiting rules, implementing bot control, setting up IP reputation filtering, and monitoring WAF metrics for security effectiveness.
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Implementing and auditing GCP VPC firewall rules to enforce network segmentation, restrict ingress and egress traffic, apply hierarchical firewall policies across the organization, and monitor firewall rule effectiveness using VPC Flow Logs.
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