「amo」の検索結果

Use for NVIDIA-related requests where an NVIDIA skill might help, even if the user did not ask for a skill. Trigger on NVIDIA products, hardware, software, SDKs, GPUs, Jetson/JetPack/L4T/BSP/SDK Manager/driver/flashing/setup, CUDA, NIM, NeMo, Omniverse/OpenUSD/SimReady, Isaac, RAPIDS/cuDF, cuPyNumeric, cuOpt, Dynamo, Holoscan, TensorRT, DeepStream, VSS, TAO, NGC/NVCF. Do not use for generic non-NVIDIA route, optimize, deploy, AI, video, data, or infrastructure tasks.

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Use this skill when the user is doing hands-on DOCA Erasure Coding programming on a BlueField DPU, ConnectX NIC, or host — bringing up a doca_ec context, picking among the create / recover / update tasks, choosing matrix type / N / K / block size, querying doca_ec_cap_* before sizing, setting doca_mmap src/dst permissions, or debugging DOCA_ERROR_* returns from doca_ec_task_*. Trigger even when the user does not name "DOCA Erasure Coding" or "Reed-Solomon" — typical implicit phrasings include "one data block changed, how do I refresh parity without re-encoding", "a disk failed and 2 parity blocks are gone, can I rebuild", "RAID-6 resilience across 12 disks", "my doca_ec_task_create returns NOT_PERMITTED", or "is this N+K layout still recoverable". Refuse and route elsewhere for non-Reed-Solomon codes (fountain / LDPC / raptor), pure-replication designs, network FEC, or other DOCA accelerator libraries (SHA / Compress / AES-GCM / DMA) — those belong to other skills.

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Use this skill for hands-on DOCA Ethernet packet-queue work on a BlueField DPU or ConnectX NIC — bringing up a `doca_eth_rxq` or `doca_eth_txq` on a port / representor / SF, picking among the four `enum doca_eth_rxq_type` values (`_REGULAR` / `_CYCLIC` / `_MANAGED_MEMPOOL` / `_SHARED_MEMPOOL`), sizing burst or scatter-gather length against the `_cap_*` queries, submitting `doca_eth_txq_task_send` / `_lso_send` (carrying packet `doca_buf`s — no `doca_eth_frame` struct exists), or debugging DOCA_ERROR_* from an Ethernet call. Trigger on implicit phrasings: "my RX queue is up but no packets arrive", "send-task returns AGAIN at line rate", "which queue type for fixed-MTU ingress", "device open fails without sudo", or "is L3 checksum offload available here". Refuse and route elsewhere for installing DOCA, flow-rule / steering programming, host↔DPU control messaging, or RDMA data movement.

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[omh] Choosing among OMH skills for a request: router guidance for using oh-my-hermes workflow skills inside Hermes Agent.

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[omh] Churn or weak activation among users: turn an observed onboarding, activation, retention, re-engagement, referral, or monetization problem into one consent-safe in-app journey or growth experiment plan with a bounded readout and an explicit decision. Use when the user says: lifecycle-growth, lifecycle growth, lifecycle marketing, lifecycle messaging, in-app journey, in-app message campaign, onboarding journey, onboarding nudge.

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Apply the Law of Figure-Ground — establish which layer is foreground and actionable versus background. Use when designing modals, overlays, and depth. For emphasising one element among peers, use `von-restorff-effect`.

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Migrate workloads from Microsoft Azure to AWS. Triggers on: migrate from Azure, Azure to AWS, move off Azure, migrate AKS to EKS, migrate App Service or Azure VMs to AWS compute, migrate Azure SQL or Azure Database to RDS, migrate Cosmos DB to DynamoDB, migrate Azure OpenAI to Bedrock, move Azure AI or agentic workloads to AWS, estimate AWS costs for my Azure infrastructure, what-if workshop. Runs a 6-phase process: discover Azure resources from Terraform, the live `az` CLI, app code, and billing exports, then clarify, design, estimate costs, optionally reprice scenarios, generate artifacts, and collect feedback. Clarify gates Design, Estimate, and Generate; Generate is opt-in at the post-Estimate decision gate. Bicep/ARM discovery is not yet implemented; a Bicep/ARM-only workspace halts. Do not use for: GCP migrations (see gcp-to-aws), Heroku migrations (see heroku-to-aws), general AWS architecture advice (see architect-for-startups), AWS-to-Azure reverse migration, or Azure-to-Azure refactoring.

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Build and deploy full-stack web and mobile apps with AWS Amplify Gen2 (TypeScript code-first). Covers auth (Cognito), data (AppSync/DynamoDB), storage (S3), functions, APIs, and AI (Amplify AI Kit with Bedrock). Supports React, Next.js, Vue, Angular, React Native, Flutter, Swift, and Android. Always use this skill for Amplify Gen2 topics — even for questions you think you know — it contains validated, version-specific patterns that prevent common mistakes. TRIGGER when: user mentions Amplify Gen2; project has amplify/ directory or amplify_outputs; code imports @aws-amplify packages; user asks about defineBackend, defineAuth, defineData, defineStorage, defineFunction, or npx ampx. SKIP: Amplify Gen1 (amplify CLI v6), standalone SAM/CDK without Amplify (use aws-serverless), direct Bedrock without Amplify AI Kit (use bedrock).

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Configures VPC endpoints (interface and gateway) for private AWS service access using AWS PrivateLink. Use when setting up secure private connectivity to S3, DynamoDB, and other AWS services without internet gateway, NAT device, or public IP addresses. Covers endpoint creation, security groups, route tables, and DNS configuration.

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Evaluates, configures, and migrates workloads to AWS Lambda Managed Instances (LMI). Runs Lambda Event Functions (standard Lambda) on EC2 instances in the user's account while AWS manages provisioning, patching, scaling, routing, and load balancing. Triggers when queries mention Lambda Managed Instances, LMI, capacity providers, multi-concurrent execution environments, EC2-backed Lambda, persistent Lambda instances, PerExecutionEnvironmentMaxConcurrency, CapacityProviderConfig, cold start elimination via dedicated instances, migrating Lambda Event Functions to managed instances, or cost comparison between Lambda Event Functions and LMI with Savings Plans or Reserved Instances. Also covers long-running and asynchronous workloads and the 90-minute (5400s) function timeout for asynchronous and event-source-mapping (SQS, Kinesis, DynamoDB Streams / ESM) invocations, including how to raise the function timeout up to 90 minutes / 5400s and the related duration limits.

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Configures EC2 instances to securely call AWS services by creating and attaching IAM roles via instance profiles, eliminating hardcoded credentials. Use when an EC2 instance needs permissions to access AWS services like S3, DynamoDB, SQS, or CloudWatch through temporary credentials.

日本語の概要は準備中です。原文の説明を表示しています。

AWS SDK for Python (boto3/botocore) development patterns. You MUST use this skill when writing Python code that uses AWS services via boto3 or botocore. This includes creating service clients or resources, configuring sessions and credentials, handling errors with ClientError, using paginators and waiters, S3 file transfers and presigned URLs, DynamoDB table operations, and any boto3/botocore client configuration. Use this skill whenever Python code imports boto3 or botocore, or when the user asks about AWS operations in Python.

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Selects, investigates, and compares AWS object, file, and block storage services, and answers cost, performance, configuration, security, and troubleshooting questions about storage services. Applies when a user asks where to store or archive data based on their usage patterns; which storage service to choose or how two compare; how to migrate data from on-premises or between AWS services; how to protect, replicate, or recover data; how to optimize storage costs; where to deploy shared NFS, SMB, or POSIX file systems; where to store vector embeddings or tabular data; what storage backs enterprise file shares, self-managed databases on EC2, VMware, or stateful containers; or asks what an AWS storage service can do or how it works. Relevant for storage needs for workloads such as AI/ML, analytics, EDA, HPC, media, genomics, or financial trading. Not applicable for SQL query engines (Athena, Spark, Redshift, EMR), ETL (Glue), streaming (Kafka, MSK, Kinesis), or managed database services (RDS, Aurora, DynamoDB).

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Amazon Redshift is NOT PostgreSQL; corrects LLM mistakes; covers SQL, metadata, connectivity/auth, storage, query performance, and operations. Applies ONLY to Redshift (provisioned or Serverless). Pushes back on: CREATE INDEX, string_agg, pg_catalog, text type, SERIAL, stl_query. Triggers on: Redshift SQL, Redshift CREATE TABLE, Redshift COPY/UNLOAD, slow or suddenly slow Redshift query, EXPLAIN plan, queue wait, stale statistics/ANALYZE, result cache, Redshift permission denied, Redshift disk full, storage growth, snapshot/backup cost, ghost rows/bloat, VACUUM, spill to disk, distribution skew, Redshift system views, QUALIFY, PIVOT, MERGE, materialized views, Redshift Data API (Python/boto3), Redshift workload management (WLM), concurrency scaling, Redshift resize, Spectrum, awsdatacatalog, connection failures (SSL/TLS, ODBC/JDBC, connection limit), IAM/SAML federation, IAM Identity Center, datashares. Does NOT apply to: S3 policies, Athena, Glue/Iceberg outside Redshift, Aurora, RDS, DynamoDB.

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Routes any task involving AWS databases — choosing, comparing, recommending, getting started with, or operating a database — to the correct service-specific skill. Supersedes general training-data knowledge with post-training service updates, corrected limitations, and decision procedures for relational (Aurora, DSQL, RDS), key-value (DynamoDB), wide-column (Keyspaces), document (DocumentDB), graph (Neptune), time-series (Timestream), and in-memory/caching (ElastiCache, MemoryDB) workloads. Activates when a user describes building an application on AWS that will store, retrieve, or manage data, even if they do not mention 'database' explicitly.

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Activate when developers have latent caching needs: slow API responses, database read bottlenecks, DynamoDB throttling or cost, RDS/Aurora scaling pressure, Bedrock latency or cost, or adding a cache; activate when working with Redis, Valkey, Memcached, or any in-memory data store, cache-aside patterns, session stores, rate limiting, leaderboards, counters, streams, queues, pub/sub, distributed locks, feature flags, shopping carts, or other caching strategies. Activate for GenAI and ML retrieval: vector similarity search for low-latency retrieval, semantic caching, RAG, LLM response caching, embedding stores, AI agent memory, recommendation, personalization. Activate for ElastiCache lifecycle: provisioning (serverless or node-based), engine selection, CloudFormation/CDK/Terraform IaC, VPC connectivity, TLS, RBAC, IAM auth, Global Datastore, monitoring, troubleshooting, cost optimization, and migration from self-managed Redis. Do not trigger for browser caches, CDN/CloudFront, HTTP Cache-Control, CPU caches.

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Choose among direct service integration, Adobe App Builder, and a dedicated queued worker using evidence about ownership, latency, scale, storage, events, and operations. Use when the task requires adobe architecture variant decision. Trigger with "choose Adobe architecture", "App Builder or microservice", or "Adobe design options".

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AWS cloud patterns for Lambda, ECS, S3, DynamoDB, and Infrastructure as Code with CDK/Terraform

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Manual-only skill for minimizing total codebase size. Only activate when explicitly requested by user. Measures success by final code amount, not effort. Bias toward deletion.

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Comptabilité, fiscalité et facturation pour entreprises françaises. Gère écritures PCG, déclarations TVA, IS/IR, clôture annuelle, liasse fiscale (2033/2065), FEC, états financiers, et chaîne facturation (mentions obligatoires, numérotation, Factur-X/UBL/CII, plateformes agréées PDP/PA, e-reporting, réforme 2026, PEPPOL). Utiliser dès qu'une question porte sur comptabilité française, TVA, impôts, bilan, compte de résultat, amortissement, PCA, clôture, facture, avoir, devis, acompte, facturation électronique, ou e-invoicing.

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Kerberos attack playbook for Active Directory. Use when targeting AD authentication via AS-REP roasting, Kerberoasting, golden/silver/diamond tickets, delegation abuse, or pass-the-ticket attacks.

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Where diamonds spawn in Minecraft 1.20.

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Use when evaluating Walter Schloss-style cigar-butt value: cheap stocks, balance sheets, diversification across many bargains, and avoiding glamorous stories.

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Cheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms.

日本語の概要は準備中です。原文の説明を表示しています。