「framework」の検索結果

Generate AI design contract (AI-SPEC.md) for phases that involve building AI systems — framework selection, implementation guidance from official docs, and evaluation strategy

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Testing strategies and methodologies including TDD, E2E testing, and multi-framework support

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Convert existing plain or manual PyTorch training code into an NVFLARE federated job using Client API model exchange, local validation, and job export; use when the user names plain PyTorch or preliminary source inspection identifies one plain-PyTorch owner, and not for Lightning, other frameworks, deployment, POC/production lifecycle, or experiment workflows.

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Convert existing PyTorch Lightning training code into an NVFLARE federated job using the Lightning Client API patch, local validation, and job export; use only when the request names federated/NVFLARE conversion or asks multiple sites to train collaboratively while keeping each site's data local, and either names PyTorch Lightning or preliminary source inspection identifies one Lightning owner; do not use for non-federated Lightning work such as DDP, profiling, inference serving, or training-loop changes, nor for plain PyTorch, TensorFlow/Keras, other frameworks, deployment, POC/production lifecycle, or experiment workflows.

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Route open-ended NVFLARE advice and only conversion requests whose preliminary source inspection reports unresolved or conflicting ownership; never load this skill merely to inspect a concrete conversion request before selecting its detected framework converter.

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Evidence-gated workflow for MoE performance optimization in Megatron Bridge. Covers measurement contracts, the Three Walls framework, parallel folding, profiling, matched A/B tuning, and final validation.

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Use this skill when choosing or running NeMo Relay installation for the CLI, Python, Node.js, Rust, OpenClaw, Hermes, or maintained framework integrations before runtime configuration or quick-start setup.

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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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Use when porting circuits from another framework (e.g. Qiskit) into CUDA-Q kernels while preserving the source algorithm and validation fidelity.

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Golang library and framework selection — vetted production-ready options by category (web, database, testing, logging, messaging), new and experimental stdlib packages, standard-library-first tradeoffs, and maturity signals (maintenance, license, importer counts). Apply when the user asks for library suggestions, wants to compare alternatives, needs to choose a library for a specific task, or when a new dependency is being added to the project. Not for a specific library's API once chosen (→ See that library's dedicated skill, e.g. `samber/cc-skills-golang@golang-samber-lo`), nor for go.mod mechanics, upgrades, or vulnerability audits (→ See `samber/cc-skills-golang@golang-dependency-management` skill).

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Golang OpenAPI/Swagger documentation with swaggo/swag — annotation comments (@Summary, @Param, @Success, @Router, @Security), swag init code generation, framework integrations (gin, echo, fiber, chi, net/http), security definitions (Bearer/JWT, OAuth2, API key), and struct tags (swaggertype, enums, example, swaggerignore). Apply when adding or maintaining Swagger/OpenAPI docs in a Go project, or when the codebase imports github.com/swaggo/swag, github.com/swaggo/gin-swagger, github.com/swaggo/echo-swagger, github.com/swaggo/http-swagger, or github.com/swaggo/files.

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Golang application framework using uber-go/fx — fx.New, fx.Provide, fx.Invoke, fx.Module, fx.Lifecycle hooks, fx.Annotate (name/group/As), fx.Decorate, fx.Supply, fx.Replace, fx.WithLogger, and signal-aware Run(). Apply when using or adopting uber-go/fx, when the codebase imports `go.uber.org/fx`, or when wiring services with fx.New. For raw DI without lifecycle, see `samber/cc-skills-golang@golang-uber-dig` skill.

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Write, review, and edit developer documentation for SDKs, libraries, and frameworks, including sites such as ai-sdk.dev and chat-sdk.dev. Use for getting-started guides, tutorials, API references, conceptual explanations, integration guides, migration guides, troubleshooting, and code examples.

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Search this repository's awesome-ChatGPT-repositories list for open-source ChatGPT and LLM projects such as RAG frameworks, agents, chatbots, CLIs, prompts, and browser extensions. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, or AI development; not for editing or adding list entries.

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Use when deploying an existing web application or API to an already-running Azure Kubernetes Service cluster. Detects the framework, generates a Dockerfile and Kubernetes manifests, validates against AKS Deployment Safeguards, and deploys with verification. WHEN: deploy app to AKS, deploy to existing AKS cluster, containerize app for Kubernetes, generate K8s manifests for Azure, set up CI/CD for AKS, my AKS deployment is failing safeguard checks, I have a Django/Express/Spring Boot app to run on AKS. DO NOT USE FOR: creating or provisioning an AKS cluster (use azure-kubernetes), assessing migration to AKS Automatic (use azure-kubernetes-automatic-readiness), or deploying to non-AKS targets like Web Apps, Container Apps, or Functions.

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Sysinternals DebugView CLI (DbgViewCli) for capturing and analyzing usermode and kernel-mode Windows debug output from the command line. USE FOR: capturing OutputDebugString output, kernel DbgPrint/KdPrint capture, boot-time debug logging, remote debug monitoring, filtering debug output by PID or process name, crash dump analysis, automated debug capture with bounded execution. DO NOT USE FOR: non-Windows platforms, application-level logging frameworks (log4j, serilog), Azure Monitor or cloud telemetry, ETW tracing (use WPR/xperf instead), user-mode crash dumps (use WinDbg). Triggers: "debug output", "DbgView", "DebugView", "kernel debug", "capture debug logs", "boot logging", "OutputDebugString", "DbgPrint", "KdPrint", "remote debug monitor", "debug capture CLI".

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Transform the agent into a Cloud Solution Architect following Azure Architecture Center best practices. Use when designing cloud architectures, reviewing system designs, selecting architecture styles, applying cloud design patterns, making technology choices, or conducting Well-Architected Framework reviews.

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Instrument browser/web apps with the Application Insights JavaScript SDK (@microsoft/applicationinsights-web). Use for Real User Monitoring (RUM) — page views, clicks, AJAX/fetch dependencies, exceptions, custom events, and browser-side GenAI agent traces correlated to backend OpenTelemetry traces. Covers SDK Loader Script and npm setup, framework extensions (React, React Native, Angular), Click Analytics, telemetry initializers, and OTel GenAI semantic conventions for agent/tool/model spans emitted from the browser.

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Perform differential expression analysis using edgeR in R/Bioconductor. Use for analyzing RNA-seq count data with the quasi-likelihood F-test framework, creating DGEList objects, normalization, dispersion estimation, and statistical testing. Use when performing DE analysis with edgeR.

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Apply Robert C. Martin-inspired architecture rules when separating business policy from frameworks, databases, UI, or infrastructure details.

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Evaluates market bubble risk through quantitative data-driven analysis using the revised Minsky/Kindleberger framework v2.1. Prioritizes objective metrics (Put/Call, VIX, margin debt, breadth, IPO data) over subjective impressions. Features strict qualitative adjustment criteria with confirmation bias prevention. Supports practical investment decisions with mandatory data collection and mechanical scoring. Use when user asks about bubble risk, valuation concerns, or profit-taking timing.

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Detect IBD-style Distribution Days for QQQ/SPY (close down at least 0.2% on higher volume), track 25-session expiration and 5% invalidation, count d5/d15/d25 clusters, classify market risk (NORMAL/CAUTION/HIGH/SEVERE), and emit TQQQ/QQQ exposure recommendations. Use after market close, before TQQQ exposure changes, or as input to FTD/market-state frameworks. Does not execute trades.

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Analyzes documents and processes against FINRA, SEC, Federal Reserve, and CFPB regulatory frameworks. Identifies compliance gaps, classifies findings by severity, and recommends remediation. Use when performing compliance audits, regulatory reviews, gap analyses, or verifying policy adherence to financial regulations.

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Use when the user asks to "draft an influencer contract", "review these agreement terms", or "build a partnership template"; produces a full influencer agreement framework (scope, compensation, usage rights, exclusivity, FTC disclosure), a clause-by-clause review with red flags, and a negotiation cheat sheet. Not for outreach negotiation before a deal exists — use outreach-manager. 达人合同/合作协议条款审查

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。