“ics”的搜索结果

Configure CRM Analytics (formerly Einstein Analytics) app sharing, dataset-level permissions, row-level security predicates, sharing inheritance, and license assignment. Trigger keywords: CRM Analytics security, row-level security predicate, dataset permissions, analytics sharing inheritance, Analytics Plus license. NOT for OWD and sharing rules — use admin/sharing-and-visibility. NOT for predicate design across many datasets — use architect/analytics-security-architecture.

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Expert-level biomechanics covering musculoskeletal mechanics, gait analysis, joint biomechanics, soft tissue mechanics, bone mechanics, and sports biomechanics.

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Manage customer and sales records in Microsoft Dynamics 365 through Rube MCP. Create contacts, accounts, leads, invoices, and support cases, update opportunities and sales orders, and retrieve or filter lead records.

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• Register companies and customer contacts
• Create, update, and filter sales leads
• Update opportunity values and expected close dates

Plan and validate tracking for marketing and product decisions. Define events, configure GA4 and Google Tag Manager, standardize campaign link labels, and calculate metrics using matching time periods to produce dependable measurement plans and findings.

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• Design a tracking plan for signups and purchases
• Investigate missing or duplicate events
• Standardize UTM labels across campaign links

Choose and track startup metrics suited to the business model and funding stage. Calculate customer acquisition cost, customer lifetime value, retention, and cash usage, then organize trends and targets for operational reviews and investor reporting.

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• Choose core metrics for a startup's stage and business model
• Calculate customer acquisition cost and lifetime value
• Review retention, growth efficiency, and cash usage

Build or tune a monitoring pipeline that learns normal user behavior from activity logs. Use Elasticsearch or OpenSearch to score unusual activity, compare colleagues in similar roles, and combine warning signs into insider threat alerts.

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• Building continuous monitoring for insider threats
• Scoring unusual logins and large downloads
• Comparing behavior across similar job roles

Plan, set up, audit, and debug analytics tracking with GA4 and Google Tag Manager. Define events and their parameters, configure conversion tracking, and investigate missing or duplicate data using structured checks and prioritized fixes.

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• Building an event tracking plan from scratch
• Auditing existing tracking for gaps and duplicate events
• Debugging events missing from GA4

Develop robotics research ideas through literature review, feasibility filtering, novelty checks, and external critique. Get ranked proposals with specific benchmarks, comparison methods, failure metrics, and simulation-first pilot plans matched to available infrastructure.

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• Exploring research topics in manipulation or navigation
• Choosing robotics ideas that fit available infrastructure
• Planning pilot studies with simulation or existing logs

Route data analysis requests to focused workflows for metric checks, business decisions, charts, dashboards, and reports. Identify usable data sources and guide the next step, with delivery choices based on the available environment.

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• Choose a workflow for a broad analytics request
• Investigate conflicting metric definitions
• Start an analysis report from uploaded data

The practice of collecting, analyzing, and acting on data to drive product decisions. Great analytics isn't about dashboards—it's about insights that lead to action. Every metric should answer a question that changes behavior. This skill covers event tracking, metrics design, dashboards, user behavior analysis, and data-driven decision making. The best analytics teams measure what matters, not what's easy to measure. Use when "analytics, metrics, tracking, dashboard, funnel, cohort, retention, events, KPI, measure, data, insights, conversion, engagement, analytics, metrics, data, dashboards, tracking, funnels, cohorts, KPIs, insights" mentioned.

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Use Nexscope market statistics capability to output a market statistics dashboard by category node, including top listing average rating, average price, BSR, sales, seller count, and new product related metrics, suitable for quickly assessing the market quality and competitive landscape of a category. Trigger when the user mentions category market statistics, market selection dashboard, market fundamentals assessment, node market quality, top product statistics, Nexscope market statistics, category statistics. Even if the user does not explicitly mention "Nexscope", if the need is to view aggregated statistical results by category node, this skill should also be triggered.

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Use when creating or managing CRM Analytics datasets: configuring dataflows, scheduling refreshes, selecting fields, handling date types, managing row-count growth, or troubleshooting stale or broken datasets. Triggers: 'dataset creation', 'dataflow schedule', 'dataflow quota', 'date field not filterable', 'dataset row limit', 'CRM Analytics data refresh', 'field type mismatch in dataset'. NOT for making an existing dataset smaller or faster — use data/analytics-dataset-optimization. NOT for choosing between Reports, CRM Analytics and Tableau in the first place — use admin/einstein-analytics-basics.

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Expert-level genomics covering whole genome sequencing, genome assembly, annotation, comparative genomics, functional genomics, single-cell genomics, and multi-omics integration.

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Gateway to 400+ bioinformatics skills from bioSkills and ClawBio. Covers genomics, transcriptomics, single-cell, variant calling, pharmacogenomics, metagenomics, structural biology, and more. Fetches domain-specific reference material on demand.

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围绕歌曲结构、押韵和演唱流畅度创作歌词，并编写Suno曲风与演唱提示，涵盖改词适配原曲节奏，以及针对AI演唱的发音调整。

• 围绕主题和记忆点创作歌词
• 修改改编歌词以适配原曲节奏
• 编写Suno曲风与演唱提示

Design a product metrics dashboard with clearly defined measures, data sources, charts, targets, and alert thresholds. The skill produces a Markdown specification that also covers dashboard layout, review schedules, and responsibilities for responding to alerts.

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• Defining product KPIs and their calculation rules
• Reviewing whether existing metrics support decisions
• Planning dashboard charts and layout

Investigate slow TPU training on GKE by comparing diagnostic events with one-minute monitoring metrics. Separate memory or CPU bottlenecks from hardware and network issues, and identify the appropriate next steps.

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• Investigating slower TPU training without pod crashes
• Checking PERFORMANCE_DEGRADATION events
• Separating resource bottlenecks from infrastructure issues

Diagnose failures in GKE HorizontalPodAutoscaler (HPA), which adjusts Pod counts automatically. Investigate missing metrics, unexpected scaling behavior, and slow reactions, then receive proposed configuration fixes or commands for review before deployment.

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• Investigating unknown metrics and HPA errors
• Diagnosing workloads that will not scale up or down
• Troubleshooting scaling to and from zero

Collect and update 68 US economic and social indicators, then summarize trends over ten, five, two, and one years. Produce a report covering relationships between indicators, unusual patterns, and topics that warrant further research.

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• Refreshing US economic and social indicators
• Comparing short- and long-term economic trends
• Examining relationships across prices, jobs, and housing

Build and maintain Elasticsearch search and analytics systems with guidance on queries, field types, and aggregations. Plan index migrations, automate data retention, diagnose cluster allocation problems, and investigate slow searches.

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• Designing full-text search and autocomplete
• Aggregating logs and time-series data
• Planning index migrations and data retention

Quickly look up SaaS financial metrics, including recurring revenue and customer acquisition costs. Get definitions, formulas, benchmarks, and warning signs, plus reminders of which metrics matter when reviewing features, pricing, acquisition channels, or business health.

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• Looking up NRR formulas and benchmarks
• Preparing a SaaS metrics sheet for a business review
• Checking metrics before expanding an acquisition channel

Guides migration, provisioning, search, log-analytics, trace-analytics, and Agentic AI Assistant workflows for Amazon OpenSearch Service and Serverless across six capabilities — migration (Solr/ES/self-managed into AOS/AOSS, schema/query translation, sizing, cutover); provisioning (domain + AOSS lifecycle, upgrades, FGAC, monitoring); search (vector / semantic / hybrid / RAG with Bedrock); log-analytics (PPL, OSI, anomaly detection, Dashboards); trace-analytics (OTel spans, service maps, Data Prepper); ai-assistant (natural language data exploration, incident investigation, root cause analysis). Triggers on OpenSearch, AOS, AOSS, Elasticsearch, Solr, vector/k-NN/semantic/hybrid search, RAG, log analytics, PPL, trace analytics, ISM, FAISS, HNSW, Migration Assistant, UltraWarm, OR1, query my data, analyze logs, investigate errors, root cause analysis.

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Designs complete research plans that integrate clinical variables with multi-omics data from a user-provided biomedical direction. Always use this skill whenever a user wants to design, scope, or structure a study that combines clinical variables with transcriptomics, proteomics, metabolomics, epigenomics, or related omics layers for mechanism interpretation, biomarker development, risk stratification, treatment-response analysis, or translational use. It should define the clinical use case, alignment across data layers, feature-reduction and fusion logic, modeling route, mechanism-interpretation layer, validation ladder, and four workload configurations (Lite / Standard / Advanced / Publication+). Never fabricate datasets, accession numbers, sample counts, metadata completeness, platform 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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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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