Skill UI

Provides Dataverse Python SDK snippets for installation, interactive authentication, CRUD, bulk operations, paging, and optional file uploads aligned with official guidance.

Connects to Google NotebookLM to query your uploaded documentation via Gemini’s source-grounded answers, automating authentication, notebook management, and question workflows through the provided run.py wrapper.

This skill provides comprehensive automation for managing OneDrive file lifecycles. Users can perform advanced operations including searching across metadata and content, uploading and downloading files, organizing folders, creating share links, and granularly managing permissions for specific users. It utilizes a structured workflow approach via Rube MCP, making it ideal for automating business processes involving cloud document storage and collaboration.

This skill automates the entire process of creating and integrating a DingTalk application and binding a QwenPaw bot. It utilizes a headed browser mode and manages complex user flows, including pausing for manual login confirmation and ensuring all configuration changes are properly published. It supports customizing app details, uploading required images, and setting up the bot capability, making the setup process seamless and robust.

Automates TikTok content creation via Rube MCP (Composio) by uploading videos/photos, managing published posts, and checking profile stats through the toolkit’s sequence of upload, publish, status polling, and profile APIs.

This comprehensive toolkit automates critical Webflow operations, including managing CMS collections (create, update, delete), site publishing, page inspection, and asset uploads. By connecting via Rube MCP, it allows developers to programmatically interact with Webflow's backend, making it ideal for implementing automated content workflows, CI/CD pipelines, and large-scale content management systems.

Automates YouTube workflows through the Rube MCP/Composio toolkit, covering uploads, playlist management, content search, analytics, subscriptions, and comments while respecting tool schemas and quota-aware practices.

Acontext serves as a robust memory layer for production-grade AI agents. It provides persistent sessions, disk-based storage, and sophisticated learning spaces that distill complex conversations into reusable, structured skills. Users can manage the entire system—from project setup and login to skill uploading—via a powerful Command Line Interface (CLI) and API, significantly enhancing agents' contextual understanding and long-term knowledge retention.

A comprehensive guide to diagnosing and fixing performance bottlenecks when using Qdrant. Covers optimizing slow uploads, resolving stuck optimizers, and tuning HNSW parameters, including best practices for sharding, bulk loading, and multi-tenant indexing to ensure efficient vector search performance.

This guide identifies and corrects the most common programming mistakes and anti-patterns when integrating with Adobe APIs. It covers critical topics such as migrating from deprecated JWT to OAuth, implementing token caching, handling asynchronous job polling, and secure file uploads. Essential reading for building robust, production-ready Adobe integrations.

A comprehensive tool for managing annotation datasets, supporting full CRUD operations, label management, and advanced export functionality. It specifically handles COCO format export and facilitates uploading datasets to platforms like Kaggle, streamlining the data pipeline for AI model development.

Detects goal hijacking vulnerabilities where malicious instructions are hidden within external content sources processed by the agent, such as retrieved documents (RAG), uploaded files, or web page content. This skill simulates these attack vectors to ensure the agent only uses the provided context for the stated task and does not execute embedded hidden commands.