382건 · 관련도순
Azure Application Insights SDK for .NET. Application performance monitoring and observability resource management. Use for creating Application Insights components, web tests, workbooks, analytics items, and API keys. Triggers: "Application Insights", "ApplicationInsights", "App Insights", "APM", "application monitoring", "web tests", "availability tests", "workbooks".
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Plan, deploy, operate, and troubleshoot multi-rack (rack scale) deployments of Azure Local — preintegrated racks scaling to hundreds of machines, built on Network Fabric Controller, Cluster Manager, SAN storage, and managed network fabric. Use for the Microsoft.NetworkCloud and Microsoft.ManagedNetworkFabric control plane. NOT for standard 1-16 node Azure Local, and NOT for rack-aware clusters (two racks as availability zones, up to 8 nodes, synchronous replication) — those are standard scale. WHEN: multi-rack, rack scale Azure Local, aggregation rack, compute rack, Network Fabric Controller, NFC, Cluster Manager, network fabric, isolation domain, az networkcloud, az networkfabric, multi-rack logical network, multi-rack Arc VM.
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Azure Resource Manager SDK for Microsoft Playwright Testing in .NET. Use for MANAGEMENT PLANE operations: creating/managing Playwright Testing workspaces, checking name availability, and managing workspace quotas via Azure Resource Manager. NOT for running Playwright tests - use Azure.Developer.MicrosoftPlaywrightTesting.NUnit for that. Triggers: "Playwright workspace", "create Playwright Testing workspace", "manage Playwright resources", "ARM Playwright", "PlaywrightWorkspaceResource", "provision Playwright Testing".
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Azure Resource Manager SDK for Fabric in .NET. Use for MANAGEMENT PLANE operations: provisioning, scaling, suspending/resuming Microsoft Fabric capacities, checking name availability, and listing SKUs via Azure Resource Manager. Triggers: "Fabric capacity", "create capacity", "suspend capacity", "resume capacity", "Fabric SKU", "provision Fabric", "ARM Fabric", "FabricCapacityResource".
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Predicts ADMET properties using ADMETlab 3.0 API or DeepChem models. Estimates bioavailability, CYP inhibition, hERG liability, and 119 toxicity endpoints with uncertainty quantification. Filters for PAINS and other structural alerts. Use when filtering compounds for drug-likeness or prioritizing leads by predicted safety.
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Use when the user asks to "optimize my Shopping feed", "fix product disapprovals", "improve product titles/attributes", or "build feed-driven PMax asset groups"; audits and rewrites the Shopping/Performance Max product feed — title/description patterns, required and recommended attributes, GTIN/availability/price hygiene, disapproval triage, and feed-driven asset-group / listing-group structure — informing the ROAS O (Offer) dimension. Not for text ad copy — use ad-creative-builder; not for scoring the account or the RQS — use ad-account-auditor. 商品Feed优化/购物广告Feed/商品标题优化/商品禁投修复
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Creates a production-ready VPC with public and private subnets across multiple Availability Zones, including internet gateway, NAT gateways, route tables, and security groups following AWS Well-Architected principles. Use when deploying multi-AZ VPC infrastructure with automatic CIDR planning and DNS resolution.
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Configures AWS Application Recovery Controller (ARC) for operational resilience: routing controls with safety rules for cross-Region failover, and zonal shift / zonal autoshift for AZ-impairment recovery. Applies when setting up failover routing, configuring safety rules, enabling zonal shift, or configuring zonal autoshift with practice runs. Also applies when shifting traffic out of a specific Availability Zone (AZ) for an ALB/NLB or other resource. For a broader "an AZ is impaired, what is my response across services" question, see aws-resilience-lifecycle. Does not apply to Resilience Hub setup or FIS experiments.
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Designs a resilience program: how to structure and standardize resilience policies across an organization, team, or portfolio (tiered policy model with availability/RTO/RPO targets and DR approach selection), and how often to run resilience activities (operational cadence). Applies when the user asks how to structure policies org-wide, what tiers/targets to set, which DR approach fits a tier, or how frequently to run assessments, FIS experiments, GameDays, or autoshift practice. Does not apply to creating or configuring a specific policy or resource for a single workload (use resilience-hub-getting-started), to step-by-step lifecycle execution (see aws-resilience-lifecycle), or to service-specific setup.
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Sets up AWS Resilience Hub v2 from scratch: creates resilience policies with SLO targets, registers systems and user journeys, onboards services with input sources, and runs a first failure mode assessment. Applies when the user wants to get started with Resilience Hub v2, create a policy, onboard a service, or run an assessment — including creating one concrete policy with specific availability/RTO/RPO targets and a DR approach for a single service (even a tier-1 one). Does not apply to FIS experiments or ARC routing controls.
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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.
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Instrument an Algolia integration for actionable availability, latency, freshness, relevance, and event-health signals. Use when defining dashboards, alerts, traces, or service objectives. Trigger with "monitor Algolia", "Algolia metrics", or "search observability".
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Google Calendar CLI for listing calendars, viewing/creating/updating events, and checking availability.
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Generates creative domain name ideas for your project and checks availability across multiple TLDs (.com, .io, .dev, .ai, etc.). Saves hours of brainstorming and manual checking.
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Design scalable distributed systems using structured approaches for load balancing, caching, database scaling, and message queues. Use when the user mentions "system design", "scale this", "high availability", "rate limiter", "design a URL shortener", "design Twitter", "design Uber", "design a news feed", "system design interview", "capacity planning", or "distributed architecture". Also trigger when estimating infrastructure requirements, choosing between microservices and monoliths, or designing for millions of concurrent users. Covers common system designs (TinyURL, feeds, chat) and back-of-the-envelope estimation. For data fundamentals, see ddia-systems. For resilience, see release-it.
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Design data systems by understanding storage engines, replication, partitioning, transactions, and consistency models. Use when the user mentions "database choice", "which database should I use", "SQL or NoSQL", "replication lag", "partitioning strategy", "consistency vs availability", "stream processing", "ACID transactions", "eventual consistency", "my queries are slow at scale", or "data is inconsistent across replicas". Also trigger when choosing a datastore, designing data pipelines, or debugging distributed-system consistency issues. Covers data models, batch/stream processing, and distributed consensus. For system design, see system-design. For resilience, see release-it.
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Google API integration for blog performance: PageSpeed Insights, CrUX Core Web Vitals with 25-week history, Search Console performance, URL Inspection, Indexing API, GA4 organic traffic, NLP entity analysis for E-E-A-T, YouTube video search for embedding, and Google Ads Keyword Planner. Progressive feature availability based on credential tier (API key, OAuth/service account, GA4, Ads). Shares config with claude-seo at ~/.config/claude-seo/google-api.json. Use when user says "google data", "page speed", "core web vitals", "search console", "indexation", "GA4", "keyword research", "nlp entities", "blog performance", "youtube search", "google api setup".
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Automate Google Calendar events, scheduling, availability checks, and attendee management via Rube MCP (Composio). Create events, find free slots, manage attendees, and list calendars programmatically.
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Converts LabArchives notebook data, entry metadata, and authorized ELN exports into manuscript-ready academic writing outputs such as Methods sections, data-availability statements, reproducibility appendices, experiment timelines, and submission support notes. Optional bundled scripts can be used to collect or validate source notebook data before writing.
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Designs complete single-cell research plans from a user-provided biomedical direction. Always use this skill whenever a user wants to design, scope, or structure a single-cell study — including disease-focused, mechanism-focused, biomarker-focused, translational, perturbation-inspired, or validation-aware projects. It should define the research question, choose the best-fit study pattern, recommend sample grouping logic, suggest reference datasets as examples only, specify the core analysis modules, propose a validation ladder, and output four workload configurations (Lite / Standard / Advanced / Publication+). Never fabricate datasets, sample metadata, accession numbers, cohort availability, cell-type labels, external validation resources, or literature references. Always include the mandatory Dataset Disclaimer immediately before any workflow section that mentions datasets or public resources.
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Designs retrospective or prospective clinical cohort study protocols for biomedical and clinical research. Always use this skill when the user needs a cohort-based study plan rather than a general study idea, evidence summary, or mechanistic experiment design. Focus on cohort appropriateness, enrollment logic, baseline time-zero definition, follow-up structure, endpoint definition, variable collection, confounding control, and a coherent primary statistical analysis line. Do not invent data availability, follow-up completeness, outcome ascertainment quality, sample size adequacy, or causal interpretability.
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Designs complete integrated research plans for bulk transcriptomics, proteomics, metabolomics, and related omics from a user-provided biomedical direction. Always use this skill whenever a user wants to design, scope, or structure a bulk multi-omics or single-omics-plus-clinical study — including disease-focused, mechanism-focused, biomarker-focused, stratification-oriented, or translational projects. It should define the research question, choose the best-fit study pattern, recommend example datasets as reference candidates only, specify the core analysis modules and method choices, propose a validation ladder, and output four workload configurations (Lite / Standard / Advanced / Publication+). Never fabricate datasets, accession numbers, sample counts, metadata completeness, cohort availability, assay coverage, literature references, PMIDs, DOIs, or validation status. Always include the mandatory Dataset Disclaimer immediately before any workflow section that mentions datasets or public resources.
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Assesses whether a medical research topic is worth starting now by separating true novelty from pseudo-novelty, auditing real feasibility under stated resource constraints, and forcing a concrete start / narrow / redesign / stop decision. Always require explicit assumptions and never fabricate references, datasets, resource availability, precedent studies, or publication claims.
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Use for parsing structured unit commitment input data from JSON, CSV, benchmark cases, spreadsheets, databases, or nested tables; finding fields for time periods, resources, load, reserve, generator limits, initial conditions, startup data, renewable availability, and production costs without assuming one source-specific schema.
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