Skill UI

A comprehensive automation toolkit for managing and executing Mailchimp email marketing workflows. It allows users to programmatically create, set content for, and send campaigns; manage entire audiences and lists; perform detailed subscriber lifecycle operations (add, update, segment); and analyze performance metrics. Ideal for marketing automation specialists and developers needing structured API access to Mailchimp. *Prerequisites include Rube MCP connectivity.*

A comprehensive automation toolkit for Mixpanel product analytics, accessible via Rube MCP. Automate key data tasks including event aggregation, detailed segmentation, conversion funnel analysis, user profile management, cohort tracking, and running custom JQL queries. Ideal for data analysts and product managers needing to deeply analyze user behavior patterns.

Automate Intercom customer-communication workflows via Composio’s Rube MCP toolkit, letting you list, search, reply, assign, close, and manage conversations plus contacts, admins, segments, and companies after fetching current tool schemas and confirming an active Intercom connection.

Orchestrate Segment customer-data actions through Rube MCP and Composio, covering event tracking, user identification, grouping, page views, batch dispatches, alias merges, and source management while always refreshing schema info first.

Histolab is a specialized Python library for digital pathology research, enabling robust processing of Whole Slide Images (WSI). It automates complex workflows including tissue detection, sophisticated segmentation, and flexible tile extraction from various formats (SVS, TIFF). This tool is crucial for preparing structured, high-quality datasets required for deep learning models and advanced computational pathology analysis.

PathML is a comprehensive Python framework designed for computational pathology workflows. It supports end-to-end analysis of Whole Slide Images (WSI), including loading 160+ proprietary formats, performing advanced stain normalization and tissue segmentation, constructing spatial cell graphs, and training deep learning models (e.g., HoVer-Net) for multiplex immunofluorescence and spatial proteomics. Ideal for large-scale biomedical image analysis.

A comprehensive guide for optimizing query latency in Qdrant. This resource explains advanced performance tuning techniques, focusing on critical resource management like RAM utilization, segment count adjustments, and HNSW parameter tuning. It details strategies for scaling, quantization, and hardware considerations (e.g., local NVMe) to ensure consistently low-latency search performance, and outlines common pitfalls to avoid.

This guide provides comprehensive strategies for managing version upgrades and handling breaking changes related to the Fathom AI meeting assistant API. It includes TypeScript examples for detecting schema drift, migrating old transcript formats to new speaker-attributed segments, and implementing robust rollback mechanisms, ensuring stable integration into downstream analytics and CRM systems.

This workflow provides comprehensive methods to manage Intercom contacts, covering the full lifecycle from anonymous leads to identified users. Users can create, search, update, merge leads into users, and manage custom attributes and segments. Ideal for building robust CRM features, synchronizing user data, or implementing advanced contact search capabilities in a SaaS application.

A comprehensive tool for creating high-quality training datasets for custom object detection and segmentation models. It supports multiple advanced annotation methods including BBox drawing, SAM2 pixel-perfect segmentation, and DINOv3 visual grounding. Features include AI auto-detection, object tracking, and standardized COCO format export, streamlining the entire data pipeline from capture to training.

Implements a robust data pipeline for handling large documents with the Grammarly API. This utility manages text chunking to comply with API character limits (max 100k), processes text in manageable segments, and aggregates multiple scoring metrics (like correctness, clarity, and tone) into a single, comprehensive report. Ideal for large-scale content analysis and data ingestion.

This comprehensive workflow manages the entire customer data lifecycle within Klaviyo. It allows users to create, update, and upsert detailed customer profiles (including LTV, properties, and contact info), manage target lists, and securely handle subscriptions. It is critical for syncing CRM or website data to enable advanced segmentation and personalized email/SMS marketing campaigns.