Skill UI

This advanced workflow executes sophisticated web data gathering tasks. It supports three primary functions: LLM-powered structured data extraction using custom JSON schemas or prompts; efficient batch scraping of multiple known URLs; and rapid site mapping to discover all reachable URLs on a domain. Use this when you require reliable, typed data structures rather than raw markdown content.

This utility collects comprehensive diagnostic data for troubleshooting Firecrawl issues. It automatically checks environment variables, verifies API connectivity, captures SDK versions, gathers recent error logs, and runs diagnostic scrapes. This is essential for generating complete, redacted support tickets when encountering persistent or hard-to-reproduce bugs.

This comprehensive guide details how to set up a robust, local development environment for Firecrawl integrations. It utilizes self-hosted Docker containers and Redis to eliminate reliance on paid API credits during development. The setup supports both unit testing (with mocked SDK) and full integration testing against the local instance, ensuring a seamless and efficient workflow for scraping and web data extraction projects.

This utility collects comprehensive diagnostic evidence for Fireflies.ai integration issues. It captures environment details (Node/Python versions, OS), checks API connectivity, gathers account metadata, and pulls recent transcript metadata. The output is a safe, redacted bundle ideal for submitting support tickets or troubleshooting persistent platform problems.

This resource provides production-ready, type-safe GraphQL client patterns for integrating with the Fireflies.ai API in both TypeScript and Python. It addresses critical engineering concerns such as robust error handling, managing singletons, implementing multi-tenant support, and ensuring structured data validation using best practices.

Automates fixture generator tasks for test automation, offering best-practice guidance, ready-to-use code/configuration, and validation for unit, integration, and mocking scenarios.

Leverage the Gamma API to rapidly generate diverse, professional content formats, including interactive presentations, detailed documents, and modern webpages. This skill supports comprehensive parameter control, allowing users to define content, select specific themes, dictate image styles, control text density, and choose output formats (PDF, PPTX, etc.). Ideal for content creators who need to transform raw text prompts into polished, multi-media assets across various professional use cases.

This skill provides comprehensive automation for content workflows using the Gamma API. It allows users to generate multiple variations from a single template, support batch processing, and specify export formats (PDF, PPTX, PNG). Furthermore, it handles the retrieval of final exported files and configures detailed sharing permissions, making it ideal for structured, large-scale content distribution.

A comprehensive, step-by-step guide detailing how to safely upgrade Gamma SDK versions (supporting both Node.js and Python) and migrate between different API versions. It covers checking current versions, reviewing changelogs, handling breaking changes in code patterns, and implementing thorough testing procedures to ensure a smooth deployment.

Automates GDPR and German DSGVO workflows by scanning codebases for privacy risks, generating DPIA documentation, and tracking data subject rights requests to support compliance assessments, audits, and planning.

This comprehensive guide provides documentation and code examples for utilizing the Gemini API, Google's advanced multimodal AI platform. It enables developers to power applications with cutting-edge capabilities, including text generation, multimodal understanding (images, audio, video), function calling, and structured data output. Supports major languages like Python, JavaScript, and Go.

This tool generates comprehensive API contracts and OpenAPI specifications (3.0/3.1) from existing codebases, design documents, or schemas. It establishes a single source of truth for APIs by producing machine-readable contracts, supporting documentation, robust testing (including consumer-driven testing via Pact), and code generation. Use it when you need to define, verify, and document complex service interfaces.