「analytics」の検索結果

Monthly marketing audit and executive review. Pulls the last 30 days of source-backed marketing, analytics, SEO, CRO, content, paid media, lifecycle, reputation, and pipeline data; compares it to the previous period; summarizes strategic learning; and produces an executive report plus next-month plan. Use when "monthly audit", "monthly marketing review", "monthly report", "executive marketing review", "board-ready marketing report", "month-end audit", or any request for a 30-day marketing audit.

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Records and replays browser sessions using rrweb recording library with DOM mutation serialization. Integrates with LogRocket API and FullStory Data Export API for session analytics.

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Apache Superset is a widely adopted open-source BI platform for SQL exploration, chart building, and dashboard delivery. This skill is useful when an agent needs to query warehouse data, assemble dashboards, or explain metrics using a mature analytics interface instead of ad hoc notebook code.

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Appsmith is an open-source platform for building internal tools, dashboards, and admin panels on top of databases and APIs. It is well suited to operational workflows where agents or developers need a fast way to stand up interfaces for support, ops, analytics, or back-office tasks.

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ActivityWatch is a privacy-first, open-source automated time tracker that records application usage, browser activity, and AFK status across Windows, macOS, and Linux. With 16k+ GitHub stars, it provides detailed productivity analytics without sending data to external servers.

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Analyze LinkedIn performance and manage engagement through Publora. Use when the user asks how a LinkedIn post or account performed (impressions, reach, reactions, comments, reshares, follower growth) or wants to react, comment, reshare or resolve an @mention. Statistics run over the REST API, engagement over MCP tools. Not for creating posts (use linkedin-post).

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Strategic product leadership guidance for SaaS and technology companies. Covers product strategy, roadmap planning, product discovery, user research, growth product management, platform strategy, product analytics, and product launches. Use when defining product vision, prioritizing features, conducting discovery, analyzing metrics, or launching products. Use for "product strategy", "roadmap planning", "feature prioritization", "product discovery", "product metrics", "PRD writing".

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Use for analytics and data pipelines. Triggers: ETL, ELT, data quality, SQL optimization, schema drift, backfill, 데이터 파이프라인, 데이터 품질, 백필.

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Use when analyzing published content (blog posts, social media, newsletters) for sentiment, structural quality, hook effectiveness, readability, topic classification, and engagement correlation. Invoke for daily post analysis, content audits, or engagement driver identification.

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Design or improve data visualizations, charts, and data presentation interfaces. Use when the user asks to add charts, build dashboards, visualize data, choose chart types, make data accessible, or present metrics and analytics.

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Drive X/Twitter from the CLI (read, post, DM, lists, communities, Grok, scheduling, analytics). Use when an agent needs to read or act on X/Twitter. Every command prints one JSON envelope.

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Coordinate SEO, LLM-readable site architecture, UX, content, monitoring, security, and external authority work as a task-plan-driven sequence. Use this skill when the user asks to plan, execute, validate, or route multi-skill website growth work; asks what to do next across semantic core, URL structure, internal linking, schema, llms.txt, UX journeys, analytics, citation monitoring, or white-hat link placement; or wants a central architect that preserves evidence, alarms, handoffs, and tests.

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Analyze credential-free public website monitoring evidence from server access logs, HTTP fetches, robots/llms/sitemap checks, and exported summaries while protecting raw IP and private query data. Use this skill when the user asks whether crawlers or AI bots reached a site, whether public SEO/LLM discovery files respond, or how to separate observed facts from unknown Search Console, rank, analytics, or citation claims.

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Use when the user needs to scope, write, or audit a product spec — a PRD, feature spec, user stories, acceptance criteria, or a "spec this out"/"break this into stories"/"definition of done" request — or wants an existing spec reviewed for gaps and anti-patterns. Triggers whenever a feature idea needs to become structured requirements that align a team on what to build. For the analytics behind success metrics, use data-analysis; for the technical design, use software-architect.

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Use when the user needs to design, run, or audit product or GTM analytics — metric hierarchies and north stars, funnels, cohort retention, churn, pipeline velocity, forecasting, lead scoring, NRR, A/B tests, or analytical SQL — or uploads a dataset to analyze. Triggers on questions like "why did activation drop", "is this metric meaningful", "review my dashboard", or "what should I measure". For writing the spec that defines a feature's success metrics, use product-spec.

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Organize, track, and value a trading card game collection. Covers inventory methods, storage best practices, grade-based valuation, want-list management, and collection analytics for Pokemon, MTG, Flesh and Blood, and Kayou cards. Use when starting a new collection and setting up inventory tracking, cataloging an existing collection that has grown beyond casual knowledge, valuing a collection for insurance or sale, or deciding which cards to submit for professional grading based on value potential.

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Deploy ShinyProxy for hosting multiple containerized Shiny applications. Covers ShinyProxy Docker deployment, application.yml configuration, Shiny app Docker images, authentication, container backends, usage tracking, and scaling. Use when hosting multiple Shiny apps behind a single entry point, needing per-app authentication and access control, deploying Shiny apps as isolated Docker containers, or scaling beyond single-app deployment with usage analytics and audit logging.

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Deploy and configure an API gateway (Kong or Traefik) to handle API traffic management, authentication, rate limiting, request/response transformation, and routing. Covers plugin configuration, upstream services, consumer management, and integration with existing infrastructure. Use when multiple backend services need a unified API endpoint, when centralized authentication or rate limiting is required, when implementing API versioning, or when needing detailed analytics and load balancing for microservices.

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Connect to and query ClickHouse (a local server or a ClickHouse Cloud service) from the terminal. For ClickHouse Cloud analytics, use the configured direct ClickHouse Query API endpoint with per-user CH_API_KEY and CH_API_SECRET credentials; do not use clickhousectl cloud service query. For local or host/port servers, use clickhousectl local client. Use when the user wants to run SQL against ClickHouse, explore schemas and tables, inspect Cloud services, or authenticate. For building a local dev environment or deploying to Cloud, defer to the official ClickHouse skills (see Scope).

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Act as an interactive data analyst for ClickHouse-backed analytics. Use when the user asks questions about internal data, metrics, dashboards, telemetry, active users, revenue, funnels, trends, distributions, or wants an analyst-style conversation, ad hoc SQL, charts, or a data export against ClickHouse (local or ClickHouse Cloud).

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Read project data documentation (data dictionaries, dbt manifests, model docs, column descriptions, lineage, metric definitions) before writing analytics SQL. Use for mapping business and product terms to concrete models and columns.

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Create standardized charts and visual assets from analytics query results. Prefer dependency-free plain HTML/CSS/JavaScript/SVG for interactive exploratory charts; use local plotting tools such as matplotlib, seaborn, or Plotly when static/report-ready exports or specialized charting libraries are more appropriate. Use for trends, comparisons, distributions, report assets, CSV-to-chart work, and presentation-ready data visuals.

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。

Act as an interactive data analyst for ClickHouse-backed analytics. Use when the user asks questions about internal data, metrics, dashboards, telemetry, active users, revenue, funnels, trends, distributions, or wants an analyst-style conversation, ad hoc SQL, charts, or a data export against ClickHouse (local or ClickHouse Cloud).

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Query Windsor.ai business data across marketing, sales, CRM, ecommerce, finance, and analytics connectors. Use when users need dashboards, reports, data visualization, schema exploration, or connector-backed test data from Windsor.ai.

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。