Skill UI

Provides automated guidance for ab test analyzer workflows, covering SQL queries, visualization, statistical analysis, and BI validation so teams can run reliable experiments within data analytics contexts.

Auto-activating aggregation helper skill for data analytics, following best practices for SQL, visualization and BI workflows, guiding queries/configs, and validating outputs.

Automate Amplitude analytics tasks through Composio’s Rube MCP toolkit, covering event ingestion, user activity, property management, cohorts, and schema discovery before each call.

Automate Amplitude analytics tasks through Composio’s Rube MCP toolkit, covering event ingestion, user activity, property management, cohorts, and schema discovery before each call.

Guides teams through assessing business goals, designing measurement plans, and implementing GA4/GTM tracking so marketing and product decisions rely on validated events, UTM strategies, and clean conversions.

Guides teams through assessing business goals, designing measurement plans, and implementing GA4/GTM tracking so marketing and product decisions rely on validated events, UTM strategies, and clean conversions.

Auto-activating data analytics skill that guides anomaly detection tasks, covering SQL, visualization, statistical analysis, and business intelligence best practices.

A comprehensive Python SDK for accessing Azure AI Language service capabilities. It enables advanced Natural Language Processing (NLP) features, including sentiment analysis, named entity recognition (NER), key phrase extraction, language detection, and sensitive PII detection. Ideal for building sophisticated text analysis applications and data pipelines.

A comprehensive Python SDK for accessing Azure AI Language service capabilities. It enables advanced Natural Language Processing (NLP) features, including sentiment analysis, named entity recognition (NER), key phrase extraction, language detection, and sensitive PII detection. Ideal for building sophisticated text analysis applications and data pipelines.

A comprehensive Java SDK client for securely and efficiently sending custom application logs to Azure Monitor. It utilizes Data Collection Rules (DCR) and Data Collection Endpoints (DCE) to manage the ingestion process. The client supports batch uploads, concurrent processing, and robust error handling, making it ideal for integrating custom logging into Azure Log Analytics workspaces.

This SDK provides a dedicated Python interface for securely sending custom logs to Azure Monitor Log Analytics workspace. It utilizes the Logs Ingestion API, supporting features like batch compression, advanced error handling, asynchronous uploads, and compatibility with various authentication models, including sovereign clouds.

This SDK provides a comprehensive Java client for interacting with Azure Monitor. It allows developers to execute powerful Kusto Query Language (KQL) queries against Log Analytics workspaces to retrieve detailed operational logs, and to query time-series metrics from various Azure resources. It supports both synchronous and asynchronous operations, making it ideal for building monitoring, auditing, and analytics features in Java applications.