'metrics' 검색 결과

Build dashboards from verified product or business data, with clearly defined metrics, charts, and useful filters. Organize the view from headline results to supporting detail, and check data freshness, numerical consistency, and dashboard behavior before handoff.

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• Monitor key product or business metrics
• Build a dashboard for recurring operating reviews
• Explore trends and differences across segments

Use for anything related to EAS Observe - adding `expo-observe` to an Expo project (AppMetricsRoot/ObserveRoot HOC, markInteractive and ObserveInteractiveMarker, the useObserve hook, the Expo Router / React Navigation integrations for per-route metrics, user-defined events via `Observe.logEvent`, error reporting via ObserveErrorBoundary and `Observe.reportError`, native crash reporting, source map upload for symbolicated stack traces, and runtime config such as sampleRate and dispatchInDebug), querying via the EAS CLI (`eas observe:metrics-summary`, `observe:metrics`, `observe:routes`, `observe:events`, `observe:session`, `observe:versions`, `observe:errors`, `observe:event`), interpreting the resulting metrics (cold/warm launch, TTR, TTI, navigation cold/warm TTR, update download, and the TTI frameRate/device/network params for triaging slow startups), or shipping an Observe integration inside a third-party package.

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This skill should be used when the user asks about "key startup metrics", "SaaS metrics", "CAC and LTV", "unit economics", "burn multiple", "rule of 40", "marketplace metrics", or requests guidance on tracking and optimizing business performance metrics.

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Use when you need to implement or improve Java metrics observability with Micrometer — including meter design, naming/tag conventions, cardinality control, timers/counters/gauges/distribution summaries, percentiles/histograms, Actuator/Prometheus integration, and metrics validation through tests. This should trigger for requests such as Improve metrics; Apply Micrometer; Add metrics observability; Refactor Micrometer instrumentation; Add Micrometer timers counters or gauges to Java services. Part of Plinth Toolkit

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Read from a UModel object-graph semantic layer with the `umctl` CLI (MCP alternative noted). Three kinds of read: (1) entities & relationships / topology (`.entity`, `.topo`) and (2) the model itself (`.umodel`, and `.entity_set` methods, including entity-linked `list_skills`) return real rows; (3) metrics & logs (`get_metrics` / `get_logs`) return an executable *plan* — PromQL / Elasticsearch DSL with the entity id pre-substituted — that you run against the backend. Against a PaaS endpoint the same calls return data rows instead of a plan. Use to query or read UModel entities, relations, topology, or model metadata; to read a service's metrics or logs; to look up services and dependencies; or to discover what objects, datasets, and methods exist. For root-cause analysis on top of these reads, see the `umodel-rca` skill. Triggers: UModel, object graph, .entity / .topo / .umodel / .entity_set, query entities, read topology, read metrics / logs, get_metrics / get_logs, list services / dependencies / datasets / skills, 实体查询, 关系/拓扑查询, 读模型, 读指标, 读日志, 查指标, 查日志, 查服务依赖.

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Produce a complete metrics definition doc — metric name, formula, data source, segmentation, SQL or event tracking spec, and what good/bad looks like. Given a product area, outputs the full metrics spec. Use when asked to "define KPIs", "metrics framework", "what should we measure", "north star metric", or "instrument this feature".

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VictoriaMetrics provider for obz. Covers all 6 metric commands (query, list, info, labels, label-values, series) using MetricsQL, a PromQL superset with extensions like keep_metric_names and range_normalize. This skill should be used when the user mentions "VictoriaMetrics", "MetricsQL", "obz metric -p vm", or needs to query metrics from a VM backend.

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Use Ahrefs through Composio to research keywords, inspect backlinks, review organic search rankings, and track domain metrics over time. Compare SEO performance across competitors or site sections with batch analysis of up to 100 URLs.

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• Inspecting backlinks and referring domains
• Finding keyword ideas with search volume and difficulty
• Comparing organic search rankings across dates

Write and review SQL for reports and metrics in a data warehouse, a store of analytical data. Applies rules for explicit columns, date filters, aggregate names, and limited exploratory results, returning SQL with a brief explanation.

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• Write SQL for report and dashboard metrics
• Calculate counts, sums, and rolling metrics
• Combine data from multiple tables

Add structured logs, performance metrics, and traces that follow requests across Python services. Establish consistent log fields and request IDs so production failures can be investigated using recorded activity and service health signals.

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• Adding searchable JSON logs
• Collecting service metrics with Prometheus
• Following requests across multiple services

Retrieve GitHub Copilot usage for an organization or enterprise through the GitHub CLI and REST API. Summarize active users, suggestion acceptance, and chat activity, with aggregate results or per-user tables for selected dates.

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• Check Copilot adoption across an organization
• Review suggestion acceptance rates and chat usage
• Compare usage across individual users

Build repeatable business reports from connected data sources or uploaded CSV and XLSX files. Define metrics and comparisons, check the calculations, deliver a concise summary and Excel workbook, and save the report definition for future or scheduled runs.

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• Comparing sales by location with last year
• Reviewing overdue receivables by age
• Tracking labor costs as a percentage of revenue

Direct finance questions to the appropriate specialist skill: financial statement analysis or SaaS operating metrics. It helps choose the right workflow for valuation, budgets, recurring revenue, churn, and customer acquisition costs.

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• Choosing the right skill for a financial analysis request
• Routing budget and valuation questions
• Routing recurring revenue and churn questions

Choose one North Star Metric, a central measure of customer value, and three to five supporting measures that influence it. Classify the business by how customers use it and assess the proposed metric against seven criteria.

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• Choosing a central measure of customer value
• Organizing the metrics a team tracks
• Comparing candidates for a North Star Metric

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

Record and query iii engine logs, traces that show how calls flow, and operational metrics. Set up reactions to incoming errors, inspect alerts, and review metrics aggregated over time windows.

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• Investigating errors through related logs and traces
• Triggering notifications when error logs arrive
• Reviewing metrics aggregated over time

Monitor model training through WandB metrics to detect invalid numbers, worsening loss, and declining evaluation results. Ambiguous trends receive a Codex review, while stopped runs retain key metrics and the reason for stopping.

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• Check loss and evaluation trends during model training
• Detect NaN values and diverging loss
• Review flat or noisy training metrics

Use Ahrefs through Composio to research keywords, inspect backlinks, review organic search rankings, and track domain metrics over time. Compare SEO performance across competitors or site sections with batch analysis of up to 100 URLs.

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• Inspecting backlinks and referring domains
• Finding keyword ideas with search volume and difficulty
• Comparing organic search rankings across dates

Track machine learning experiments with Trackio by recording training measurements, viewing live dashboards, and flagging diagnostic events. Retrieve metrics and alerts through command-line queries, with JSON output for automated monitoring and experiment review.

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• Recording training loss and accuracy
• Flagging loss spikes or stalled training
• Monitoring cloud training through a Space dashboard

Build TypeScript summary panels that combine data already fetched by other panels. Accept partial updates, wait for required fields before rendering, and update displayed metrics without additional network requests, using reusable base classes and a coordinator.

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• Combine email and stock metrics in one summary panel
• Wait for required data before showing a summary
• Update metrics using data fetched by other panels

Calculate and interpret SaaS subscription revenue, customer churn, and revenue retained from existing customers. Compare customer groups and revenue sources to uncover retention problems, explain growth, and prepare metrics for leadership discussions.

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• Preparing revenue and retention metrics for a board presentation
• Checking whether revenue growth hides customer churn
• Comparing retention by customer start date

Add team-specific evaluation criteria to plugin-eval by designing a metric pack, a set of custom checks and measurements. Create its manifest and JSON-producing script, then run it through the evaluator using a consistent output structure.

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• Add team-specific evaluation criteria
• Define custom checks and numerical metrics
• Build a metric-pack manifest and script

Design key performance indicators for business or product decisions, including definitions, calculations, targets, and measurement plans. Select supporting metrics that explain progress and guardrails that track unwanted effects on quality, cost, or other outcomes.

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• Define success metrics for a product launch
• Choose growth metrics and supporting drivers
• Set an experiment's success metric and guardrails

Print a debt-ops health summary from the metrics log, covering registration rate, hook feedback action rate, ADR creation, and AI-authored share. Use when the user asks for "debt-ops metrics", "debt health", "registry stats", or invokes $metrics. Read-only, never writes the log.

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