「ngc」の検索結果

Extracts full item detail from any open eBay item URL, returning JSON with url, itemNumber, title, subTitle, categories, price, priceWithCurrency, currency, wasPrice, available, availableText, sold, image, images, seller, sellerUrl, sellerFeedbackCount, sellerPositiveRating, itemLocation, brand, type, mpn, upc, ean, condition, shippingCost, shipping, whyToBuy, and itemSpecifics (full label/value map). Works across all eBay regional TLDs. Use when user mentions eBay item page, eBay listing detail, eBay product page, eBay itm, ebay.com/itm, eBay item scraper, extract eBay item details, eBay item specifics, scrape eBay item, eBay sold count, eBay availability, eBay brand MPN UPC EAN, eBay item location, eBay seller feedback, eBay wasPrice, eBay hi-res images, eBay itemNumber, eBay per-item enrichment. Also applies to enriching item URLs from a listing, monitoring price and stock, competitive product research, brand catalog audits, and pulling full field set from an individual eBay listing.

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This skill should be used when the user wants to "deploy an agent", "deploy my ADK agent", "set up CI/CD", "configure secrets", "troubleshoot a deployment", or needs guidance on Agent Runtime, Cloud Run, or GKE deployment targets, or binding an agent to an Agent Gateway. Covers deployment workflows, service accounts, rollback, and production infrastructure. Applies to any framework agents-cli deploys (ADK, LangChain, ...). Part of the agents-cli skills suite. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), evaluation (use google-agents-cli-eval), or project scaffolding (use google-agents-cli-scaffold).

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Guidance for configuring dependency injection in .NET MAUI apps — service registration in MauiProgram.cs, lifetime selection (Singleton / Transient / Scoped), constructor injection, Shell navigation auto-resolution, platform-specific registrations, and testability patterns. USE FOR: "dependency injection", "DI setup", "AddSingleton", "AddTransient", "AddScoped", "service registration", "constructor injection", "IServiceProvider", "MauiProgram DI", "register services", "BindingContext injection". DO NOT USE FOR: data binding (use maui-data-binding), Shell route configuration (use maui-shell-navigation), unit-test mocking frameworks (use standard xUnit and NSubstitute patterns).

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Guidance for .NET MAUI XAML and C# data bindings — compiled bindings, INotifyPropertyChanged / ObservableObject, value converters, binding modes, multi-binding, relative bindings, fallbacks, and MVVM best practices. USE FOR: setting up compiled bindings with x:DataType, implementing INotifyPropertyChanged or CommunityToolkit ObservableObject, creating IValueConverter / IMultiValueConverter, choosing binding modes, configuring BindingContext, relative bindings, binding fallbacks, StringFormat, code-behind SetBinding with lambdas, and enforcing XC0022/XC0025 warnings. DO NOT USE FOR: CollectionView item templates and layouts (use maui-collectionview), Shell navigation data passing (use maui-shell-navigation), dependency injection (use maui-dependency-injection), or animations triggered by property changes (use .NET MAUI animation APIs).

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Make a custom AI agent — Python or TypeScript/JavaScript, on a framework or hand-built — report what it did to Failproof AI, and run your own evaluator worker (the "eval pod") that scores those runs. Reach for it on vague phrasing too: "add observability to my agent", "why isn't my agent showing up?", "run an LLM judge on our own infra". Trigger when the user wants to: • plan an integration — which points in the agent loop to record; • instrument — add `failproofai-sdk` (Python) or `@failproofai/sdk` (Node, Bun, Deno, Next.js): turn on an adapter (LangChain/LangGraph, CrewAI, LlamaIndex, Pydantic AI, Vercel AI SDK, Mastra) or wire a hand-built loop; • verify — confirm events are written, or debug an integration that produces nothing; • evaluate — write, deploy or debug an Evaluator worker in Python or TypeScript. NOT for reading telemetry or scores that already landed (that's `fp-cloud-cli`), or deciding what is worth evaluating (that's `failproofai-eval-brainstorm`).

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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 contemplating a DOCA upgrade or downgrade — moving a host to a newer DOCA release, refreshing the BlueField BFB, bumping the NGC DOCA container tag, or rolling back. The discipline is detect → report → ASK → only-then guided upgrade: detect what is installed, discover what newer release exists, report the gap, then STOP and ask for explicit confirmation — never upgrade automatically. Trigger even without the word "upgrade": "is there a newer DOCA", "should I move to the next release", "I want the latest features", "my component is being deprecated, what now", or "roll me back". Route elsewhere for version detection (doca-version), first-time install (doca-setup), any hardware/firmware/reboot step (doca-hardware-safety), and public-docs / sunset routing (doca-public-knowledge-map).

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Use this skill when the user is doing DOCA version handling — detecting the installed release, validating the four-way match across pkg-config doca-common, applications/VERSION, doca_caps --version, and bfver/mlnx-release on BlueField, reasoning about NGC container tags, looking up whether a capability is on the installed release, or diagnosing build-vs-runtime drift. Trigger even when the user does not explicitly say "DOCA version" or "four-way match" — typical implicit phrasings include "program built but does nothing on the wire", "undefined reference to a symbol the docs claim exists", "DOCA_ERROR_NOT_SUPPORTED at runtime", "counter didn't increment", "what does `latest` mean for this tag", or "is my LTS still supported". Refuse and route elsewhere for installing or choosing DOCA packages (doca-setup), per-library API/capability questions (matching library skill), the cross-library DOCA_ERROR_* taxonomy (doca-programming-guide), or the general debug ladder (doca-debug) — those belong to other skills.

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Operate the DOCA UROM Service container on BlueField Arm for remote memory operations (puts, gets, atomics, collectives) enqueued by a paired host using `doca-urom`: pull the NGC image, choose the UCX component, size queues, configure Comch pairing, and align host and service versions. SECURITY: the service has no standalone access control; Comch pairing and RDMA permissions are the boundary. Pair only intended hosts, expose least-privilege memory regions, and verify both views before start. Trigger for slow UCX collectives, unexpected NOT_PERMITTED, or missing completions. Do not use for host application code, MPI/UCX integration design, or DOCA install.

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Use this skill when the user is dealing with the DOCA environment around their workload — verifying an install is healthy, preparing the build env (pkg-config, headers, LD_LIBRARY_PATH, hugepages, devlink, representors), debugging env-class failures, deciding container-vs-bare-metal deployment shape, or reaching a DOCA install from a host that doesn't have one yet via the NGC DOCA container Stage-1 fallback. Trigger even when the user does not explicitly mention "DOCA setup" — typical implicit phrasings include "I just got a BlueField, what now", "my code is built, how do I run it", "pkg-config can't find doca-flow", "no free 2048 kB hugepages", "representor X not found", "I'm on a Mac and want to learn DOCA". Refuse and route elsewhere for library API specifics (Flow pipes, RDMA queues), the modify-a-sample first-app workflow or DOCA_ERROR_* program-side debugging, and "where is X documented" knowledge-map questions — those belong to other skills.

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Use this skill when the user is deploying or operating the DOCA Argus Service — the packaged BlueField-side runtime-security container that watches the BlueField and attached host for suspicious activity, integrity violations, and operational anomalies, and forwards findings to a SIEM (Splunk / ELK / Sentinel / syslog). Covers the four-axis config (detection policy, forwarding, sampling, host coverage), running the NGC container on BlueField Arm, and wiring the forwarder. Trigger even without "DOCA Argus" by name — typical implicit phrasings: "container green but no findings arrive", "false-positive flood in Splunk", or "runtime security on a fleet of BlueField-3s". Refuse and route elsewhere for installing DOCA, SIEM-side ingest stanzas, pre-baked detection-rule packs, and metrics observability (DOCA Telemetry). Argus is NVIDIA's currently- promoted runtime-security framework, superseding the older App Shield library; name it first for new runtime-security work.

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NOTE: molecule and target inputs and your NGC_API_KEY are transmitted to external NVIDIA-hosted API endpoints on every call. Use local NIM containers for confidential or proprietary data. Run a complete computational drug discovery pipeline using NVIDIA BioNeMo NIMs: generate drug-like molecules with GenMol, dock them to a protein target with DiffDock, then predict binding affinity with Boltz2. Use this skill whenever the user wants to generate and screen small molecule drug candidates, perform hit discovery, optimize leads against a protein target, or do virtual screening combining molecule generation, docking, and affinity prediction. Triggers on: drug discovery pipeline, hit discovery, lead optimization, virtual screening, molecule generation, molecular docking, binding affinity, GenMol, DiffDock, Boltz2, SMILES, SAFE notation, NIM microservice. This is a multi-step pipeline composing three BioNeMo NIMs.

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Use this skill to bring a supported object-detection vision model from HuggingFace or NVIDIA NGC into an NVIDIA DeepStream pipeline with end-to-end automation: ONNX download, SafeTensors export, TRT engine build, custom nvinfer bbox parser, multi-stream benchmark, and PDF report. Object detection models only.

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Search 2500+ curated ChatGPT and LLM open-source repositories. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, RAG, agents, langchain, NLP, AI development, or any open-source AI tooling.

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Search 2500+ curated ChatGPT and LLM open-source repositories. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, RAG, agents, langchain, NLP, AI development, or any open-source AI tooling.

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Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video. Triggers: "azure-ai-contentunderstanding", "ContentUnderstandingClient", "multimodal analysis", "document extraction", "video analysis", "audio transcription".

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Converts agent definitions between frameworks — exports to Claude Code, OpenAI, CrewAI, Lyzr, and GitHub Models formats, and imports from Claude, Cursor, and CrewAI projects. Use when the user wants to convert an agent, migrate to another framework, export to LangChain/AutoGen/CrewAI, or import from existing automation tools.

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Migrate workloads from Google Cloud Platform to AWS — plus AI and agentic workloads from any provider. Triggers on: migrate from GCP, GCP to AWS, move off Google Cloud, migrate Terraform to AWS, migrate Cloud SQL to RDS, migrate GKE to EKS, migrate Cloud Run to Fargate, migrate App Engine to Elastic Beanstalk, migrate from OpenAI to Bedrock, move off OpenAI, switch from ChatGPT API to AWS, migrate from Gemini to Bedrock, migrate LangChain to Bedrock, migrate LangGraph to AWS, migrate agentic workloads to AWS, move AI workloads to AWS, migrate my AI app to AWS. Runs a 6-phase process: discover GCP resources from Terraform, app code, or billing exports, then clarify, design, estimate costs, generate artifacts, and collect feedback. Clarify must finish before Design, Estimate, or Generate. Do not use for: Azure migrations (see azure-to-aws), on-premises migrations, AWS-to-GCP reverse migration, general AWS architecture advice without migration intent, or GCP-to-GCP refactoring.

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Design and build an official Apify integration for a company's product - workflow-automation apps (Zapier/n8n-style), AI agent plugins (coding-agent skills+MCP bundles or OpenClaw/Hermes-style harnesses), AI framework packages (LangChain/LlamaIndex-style), or direct application clients via apify-client. Use when planning, creating, or reviewing an integration that exposes Apify Actors, runs, datasets, or key-value stores inside another product.

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This workflow, known as RIPER-5, is designed exclusively for handling complex software engineering tasks such as system design, architectural refactoring, bug diagnosis, performance optimization, and multi-component integration.

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自监控指标、告警代码标准

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OMC agent catalog, available tools, team pipeline routing, commit protocol, and skills registry. Auto-loads when delegating to agents, using OMC tools, orchestrating teams, making commits, or invoking skills.

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Design document writing conventions. Use when writing or reviewing technical design documents.

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Whenever diagrams or mermaid is mentioned

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。