Skill UI

Scans Algorand TEAL/PyTeal smart contracts for 11 platform-specific vulnerabilities such as rekeying, unchecked fees, group manipulation, and missing access controls, then reports findings with severity, suggested fixes, and optional Tealer automation.

This SDK provides comprehensive Python support for interacting with Azure Event Hubs, a high-throughput streaming platform. It allows developers to build robust data ingestion pipelines, acting as both event producers (sending data) and event consumers (receiving data). Key features include efficient batch processing, partition key management, and reliable checkpointing using Azure Blob Storage for production-grade stream applications.

This SDK provides comprehensive Python support for interacting with Azure Event Hubs, a high-throughput streaming platform. It allows developers to build robust data ingestion pipelines, acting as both event producers (sending data) and event consumers (receiving data). Key features include efficient batch processing, partition key management, and reliable checkpointing using Azure Blob Storage for production-grade stream applications.

This guide details the complete setup process for integrating with the Clay data enrichment platform. It covers obtaining the Enterprise API key, configuring webhook endpoints for data ingestion, and connecting third-party data providers (like Apollo or Clearbit). Use this when onboarding, setting up automated data pipelines, or maximizing credit savings through programmatic integration.

This guide provides a comprehensive walkthrough for setting up the Evernote SDK and implementing OAuth 1.0a authentication. It details the entire process, from acquiring API keys via the developer portal, installing the SDK (for Node.js or Python), configuring environment variables, to initializing the client. Use this skill when starting a new Evernote integration or needing to verify secure API connectivity to the Evernote Cloud.

This guide outlines how to implement robust Role-Based Access Control (RBAC) for Firecrawl scraping resources. It allows enterprises to manage multiple API keys, enforce per-team credit consumption limits, and restrict scraping to specific allowed domains (allowlisting). Use this when scaling scraping operations across various departments or services that require granular resource governance and budget tracking.

Provides minimal working examples and comprehensive instructions for querying the Fireflies.ai GraphQL API. Users can learn how to list workspace users, fetch recent meeting transcripts, and retrieve detailed summaries, including action items and keywords, using code examples in TypeScript, Python, and Bash. Ideal for initial API setup, integration testing, or learning GraphQL patterns for meeting data.

This comprehensive guide provides step-by-step instructions for setting up and authenticating with the Gamma Generate API v1.0. It covers generating the required API key, configuring environment variables, and executing initial connection tests using `curl` or code snippets in Node.js and Python. Essential for developers integrating Gamma's content generation capabilities into their applications.

This solution implements robust Role-Based Access Control (RBAC) and multi-tenancy for third-party AI services. By utilizing an application proxy layer, it allows organizations to manage multiple teams, assign separate API keys, enforce granular content policies (e.g., filtering prohibited terms), and track daily budgets. This ensures secure, governed, and scalable resource usage in enterprise environments.

Provides automated guidance and production-ready artifacts for key rotation manager workflows within advanced security scenarios.

This guide demonstrates the basic workflow for building an AI agent using a webhook trigger. The agent receives structured data (payload), utilizes an LLM to extract key information and generate a concise summary (summarization step), and finally executes an action by posting the summary to Slack or sending an email. Ideal for beginners learning about AI agent architecture, testing data flow, and implementing simple automated system notifications.

Automates designing and implementing table partitioning strategies to keep large databases performant, optimize time-series workloads, and shorten maintenance windows, with guidance on key selection, SQL scripts, and query tuning.