「cui」の検索結果

Assess portfolio risk using npx neural-trader — VaR, CVaR, Sharpe, position sizing, circuit breaker status

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。

Generates or edits images with AI models through the OpenRouter Image API (Gemini, Seedream, Recraft, GPT-Image, Riverflow). Use for photos, illustrations, artwork, concept art, visual assets, logos, and image editing or compositing from reference images. For flowcharts, circuits, pathways, and other technical diagrams, use the scientific-schematics skill instead.

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。

Configure Istio traffic management including routing, load balancing, circuit breakers, and canary deployments. Use when implementing service mesh traffic policies, progressive delivery, or resilience patterns.

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。

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.

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。

Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching experiments.

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。

Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching experiments.

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。

Unified dashboard panel pattern combining circuit breaker resilience with enhanced UI features like retry logic, state persistence, and detailed error handling.

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。

Create data fetching services with circuit breaker pattern for API resilience. Services handle fetch, cache, retry, and expose typed data to panel components.

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。

Create resilient, data-driven dashboard panels with integrated API handling and UI components, combining circuit breaker patterns with vanilla TypeScript panel architecture.

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。

Create data fetching services with circuit breaker pattern for API resilience, including a first-class pattern for building optional query parameters via URLSearchParams. Services handle fetch, cache, retry, optional filters, and expose typed data to panel components.

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。

Single cohesive workflow for creating complete dashboard panel features in vanilla TypeScript — covers project-structure exploration, server dispatch pattern detection and wiring (Express or manual http.createServer), Panel base class component authoring with CircuitBreaker resilience and localStorage persistence, panel registration in index.ts, and safe file writing (including emoji workarounds).

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。

Create resilient data fetching services with circuit breaker pattern, supporting both proxied and direct API calls. Services handle fetch, cache, retry, and expose typed data to panel components.

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。

Guides design and implementation of evolutionary modular-monolith platforms with DDD (strategic + tactical), flat-by-aggregate organization, an Anti-Corruption Layer for vendor independence, a transactional outbox for events, smart resilience (backoff with jitter, circuit breakers, idempotency), and a polished architecture HTML document with elegant SVG diagrams. Use when designing a platform or backend, defining bounded contexts, organizing modules and folders, choosing monolith vs microservices, decoupling from an external service (ERP, storage, AI), making calls resilient, adding real-time push, picking a 2026 TypeScript stack (Nx, NestJS, React), or producing an architecture document or diagram. Also triggers on 'modular monolith', 'bounded contexts', 'flat-by-aggregate', 'ports and adapters', 'architecture diagram'. Do NOT use for simple CRUD, NestJS-only deep implementation (use nestjs-modular-monolith), or pure domain-model review (use tactical-ddd).

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。

This skill is designed to help users automatically extract business data from Google Maps search results. The Agent should proactively apply this skill when the user makes the following requests searching for coffee shops in a specific city, finding dentists or medical clinics nearby, tracking competitors' locations in a certain area, extracting business leads from Google Maps lists, gathering restaurant data for market research, finding hotels or accommodation options in a region, locating specific services like coworking spaces or gyms, monitoring new business openings in a neighborhood, collecting contact information and addresses for sales prospecting, analyzing price ranges and cuisines of local eateries, getting ratings and review counts for a list of businesses, exporting local business data into a CRM or database.

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。

Hunt gRPC vulnerabilities — server reflection enabled (enumerate all services/methods), missing authentication / metadata-stripping on internal endpoints, plaintext gRPC over HTTP/2, internal endpoint disclosure, proto file leakage, gRPC-Web/grpc-gateway transcoding injection, and HTTP/2 Rapid Reset DoS (CVE-2023-44487). Use when target exposes port 50051 / 443 / 8443 / 9090 with HTTP/2, when grpcurl/grpcui detects reflection, when an Envoy or grpc-gateway proxy is fronting a microservice, or when recon reveals a microservice architecture.

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。

Quantum physics simulation library for open quantum systems. Use when studying master equations, Lindblad dynamics, decoherence, quantum optics, or cavity QED. Best for physics research, open system dynamics, and educational simulations. NOT for circuit-based quantum computing—use qiskit, cirq, or pennylane for quantum algorithms and hardware execution.

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。

Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching experiments.

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。

Generate or edit images using AI models (FLUX, Nano Banana 2). Use for general-purpose image generation including photos, illustrations, artwork, visual assets, concept art, and any image that is not a technical diagram or schematic. For flowcharts, circuits, pathways, and technical diagrams, use the scientific-schematics skill instead.

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。

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

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。

Apply Michael T. Nygard-inspired production reliability rules when designing failure handling, timeouts, retries, circuit breakers, observability, or deployment behavior.

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。

Evaluate a local pre-trade checklist before manual order entry, blocking planless, oversized, revenge-risk, market-regime-blocked, or circuit-breaker-blocked entries while journaling the decision for trader-memory-core review.

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。

Runs quantum computing workflows on AWS through Amazon Braket — discovering devices (QPUs and simulators) and their availability, building gate-model circuits and analog Hamiltonian programs, submitting quantum tasks, program sets and hybrid jobs, looking up prices, and capping spend with spending limits. Applies to any request about quantum computing, quantum hardware, quantum simulation, AHS, OpenQASM, or running a quantum algorithm on AWS.

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。

Builds and deploys containerized workloads on Elastic Kubernetes Service (EKS), Elastic Container Service (ECS), Fargate, and ECR (Elastic Container Registry). Covers general EKS knowledge, Karpenter, AWS Load Balancer Controller and leveraging various open source Kubernetes projects with EKS. Covers general ECS knowledge, task definitions, Fargate services, ECS Exec, ECS Express Mode and ECS Managed Instances. Covers general Elastic Beanstalk knowledge, Elastic Beanstalk configuration and platforms supported by Elastic Beanstalk. Covers general ECR knowledge, ECR repository setup and lifecycle policies. Includes recommending, enabling, and reading Amazon ECS Action Logs to troubleshoot control-plane failures (deployment rollback/circuit-breaker, task placement, scaling, task replacement). Applies when deploying, debugging, or optimizing containers on AWS. Should be used instead of relying on internal knowledge for these services.

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。

Analyze and design idempotency, bounded polling, per-service circuits, durable queues, DLQ/replay, degradation, and reconciliation for Adobe workloads. Use when the task requires adobe async reliability controls. Trigger with "Adobe reliability", "Firefly retry design", or "PDF job recovery".

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。