227건 · 관련도순
Use when working with Aws Sam — aWS Serverless Application Model (SAM) management. Covers template validation, local testing, build and packaging, deployment orchestration, stack inspection, log tailing, and API Gateway debugging. Use when building serverless applications with SAM, testing locally, deploying Lambda functions, or troubleshooting API Gateway endpoints.
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Use when working with Aws Rightsizing — analyze EC2, RDS, EBS, and Lambda resource utilization to identify right-sizing opportunities. Uses CloudWatch metrics with anti-hallucination rules for burstable instances, memory metrics, peak vs average analysis, and estimated monthly savings calculations.
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Use when working with Aws Cognito — aWS Cognito user pool analysis, identity pool management, authentication flow analysis, and MFA status tracking. Covers user statistics, app client configuration, password policy review, Lambda trigger inspection, and federation setup.
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Manages MongoDB Atlas Stream Processing (ASP) workflows. Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations for streaming data workloads and event processing. NOT for general MongoDB queries or Atlas cluster management. Requires MongoDB MCP Server with Atlas API credentials.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Specialized skill for building production-ready serverless applications on AWS. Covers Lambda functions, API Gateway, DynamoDB, SQS/SNS event-driven patterns, SAM/CDK deployment, and cold start optimization.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Proper Lambda function structure with error handling
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Integracao completa com Amazon Alexa para criar skills de voz inteligentes, transformar Alexa em assistente com Claude como cerebro (projeto Auri) e integrar com AWS ecosystem (Lambda, DynamoDB, Polly, Transcribe, Lex, Smart Home).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implementing AWS Security Hub to aggregate security Bul:ings across AWS accounts, enable compliance standards like CIS AWS Foundations and PCI DSS, configure automated remediation with EventBridge and Lambda, and create custom security insights for organizational risk management.
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bu skill provides step-by-step procedures for identifying and remediating Amazon S3 bucket misconfigurations that expose sensitive data to unauthorized access. It covers enabling S3 Block Public Access at account and bucket levels, auditing bucket policies and ACLs, enforcing encryption, configuring access logging, and Dağıt:ing automated remediation using AWS Config and Lambda.
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Elliptic Curve Cryptography saldırıları — ECDLP (Pollard rho/lambda, Pohlig-Hellman), Smart's attack, MOV/Frey-Rück, invalid curve, ECDSA nonce reuse, biased nonce lattice
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Diffie-Hellman key exchange ve DLP saldırıları — Pohlig-Hellman, Pollard rho/lambda, BSGS, small subgroup confinement, weak parameter detection
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Performs alchemical free-energy calculations including relative binding free energy (RBFE / FEP+) and absolute binding free energy (ABFE) via OpenFE, FEP+, GROMACS, AMBER pmemd, and OpenMM with explicit lambda window scheduling, soft-core potentials, REST2 enhanced sampling, MBAR/BAR analysis, and cycle closure validation. Compares ML alternatives (Boltz-2 affinity, DeepDock). Use when ranking analogs by binding affinity beyond docking accuracy, performing prospective lead optimization, or validating SAR predictions.
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Hono (軽量・マルチランタイム対応 Web フレームワーク) リファレンス。 Hono App, Context (c.req / c.json / c.text / c.html), HonoRequest, Routing, HTTPException、 Built-in Middleware (JWT, CORS, CSRF, Cache, Logger, Compress, Basic / Bearer Auth, Mount)、 Helpers (Cookie, Streaming, WebSocket, Factory, RPC)、 Cloudflare Workers / Deno / Bun / Node.js / AWS Lambda 対応、@hono/* アダプターパッケージ。
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Detects focal chromatin loops (point interactions / corner-dots) in balanced Hi-C and Micro-C contact maps and aggregates/validates a loop set. Covers de-novo calling with cooltools dots (HiCCUPS-style 4-background local enrichment with lambda-chunked FDR), chromosight (template-correlation), and Mustache (scale-space blob detection); aggregate peak analysis (APA) via cooltools pileup for confirmation; the depth/resolution prerequisite (de-novo needs ~5-10kb resolution = hundreds of millions to billions of valid pairs); consensus across callers and convergent-CTCF support as validation; and differential loops via union anchors plus chromosight quantify. Use when calling chromatin loops or dots from a cooler, deciding whether a map is deep enough to call de-novo vs running APA on known CTCF/cohesin anchors, building an aggregate peak pileup, comparing loops across conditions, or validating loop calls. For HiChIP/PLAC-seq/PCHi-C protein-anchored data use FitHiChIP/MAPS, not dots.
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Build Manhattan, Miami, QQ, and locuszoom-style regional plots from GWAS, TWAS, PWAS, and QTL summary statistics with correct genomic-inflation diagnostics, multi-trait overlays, lead-SNP labeling, and LD-aware regional rendering. Use when visualizing association results across the genome, comparing two traits, computing genomic inflation lambda, or zooming into a locus with LD coloring.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Performs alchemical free-energy calculations including relative binding free energy (RBFE / FEP+) and absolute binding free energy (ABFE) via OpenFE, FEP+, GROMACS, AMBER pmemd, and OpenMM with explicit lambda window scheduling, soft-core potentials, REST2 enhanced sampling, MBAR/BAR analysis, and cycle closure validation. Compares ML alternatives (Boltz-2 affinity, DeepDock). Use when ranking analogs by binding affinity beyond docking accuracy, performing prospective lead optimization, or validating SAR predictions.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Specialized skill for building production-ready serverless applications on AWS. Covers Lambda functions, API Gateway, DynamoDB, SQS/SNS event-driven patterns, SAM/CDK deployment, and cold start optimization.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Provide comprehensive techniques for penetration testing AWS cloud enprojectnments. Covers IAM enumeration, privilege escalation, SSRF to metadata endpoint, S3 bucket exploitation, Lambda code extraction, and persistence techniques for red team operations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Integracao completa com Amazon Alexa para criar skills de voz inteligentes, transformar Alexa em assistente com Claude como cerebro (projeto Auri) e integrar com AWS ecosystem (Lambda, DynamoDB, Polly, Transcribe, Lex, Smart Home).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Proper Lambda function structure with error handling
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.