Skill UI

A comprehensive guide and toolkit for optimizing and monitoring consumption-based costs across the Adobe Creative Cloud ecosystem. It provides strategies and code snippets for tracking usage (credits, transactions) for Firefly, PDF Services, Photoshop, and Lightroom APIs. Use this when implementing usage monitoring, managing billing alerts, or reducing operational expenses related to Adobe API calls.

This guide walks users through verifying the complete setup of their Fondo account. It covers essential financial checks, including synchronizing bank transactions, reviewing automated transaction categorization (payroll, software, office), and confirming eligibility and data needed for R&D tax credits. Use this when initially setting up or auditing your core financial data flow.

A comprehensive guide and setup for establishing a fast, reproducible local development loop for web scraping projects using Bright Data. It includes configuring proxy modules, implementing response caching to save credits, and setting up mocked test suites (using Vitest) for robust, isolated testing without requiring live proxy access or consuming resources.

Executes the comprehensive workflow for claiming Research & Development (R&D) tax credits through Fondo. This skill guides users through qualifying R&D expense calculation, prepares the necessary Form 6765, and manages the payroll tax offset process for startups, potentially saving up to $500,000 annually.

A comprehensive guide for startups to maximize Return on Investment (ROI) by optimizing operational costs and leveraging R&D tax credits. This skill covers strategies for improving bookkeeping efficiency, structuring employment (W-2 vs. contractor), selecting the optimal financial plan, and minimizing overall accounting complexity using Fondo's tools.

This comprehensive guide details the setup process for the Fondo platform, designed for automated startup bookkeeping, tax filing, and tracking R&D tax credits. Users must connect core financial sources, including payroll providers (e.g., Gusto, QuickBooks), corporate bank accounts (via Plaid), and expense management tools (e.g., Brex, Ramp). Following these steps ensures seamless data synchronization and compliance for US-incorporated businesses.

A comprehensive workflow for developing and testing financial applications integrated with Fondo. It enables developers to simulate or parse real Fondo exports (CSV/Accounting tools) locally, providing a fast feedback loop for building dashboards, calculating R&D credits, and analyzing burn rates without relying on live API connectivity. Supports mock data for rapid iteration and real export parsing for production validation.

This reference architecture outlines a comprehensive financial stack for startups. It centralizes core financial functions—including banking (Mercury), payroll (Gusto), revenue/expense tracking (Stripe/Brex), and advanced bookkeeping/tax services (Fondo)—into a unified data flow. It helps founders and finance teams manage everything from daily transactions to monthly closing, tax filings (like R&D credits), and generating board reports efficiently.

This skill guides the identification and search for specialized crew members (such as production controllers, costume designers, music directors) in South Asian cinema. It is essential when a question focuses on technical roles rather than just the director or lead actors. By using specific search queries on reliable databases (like IMDb or Wikipedia) after identifying the film, users can efficiently locate detailed production credits.

This skill guides users through optimizing corporate travel spending using the Navan platform. It covers analyzing historical booking data via REST API, configuring granular travel policies (flight/hotel caps), enforcing negotiated rates, tracking unused travel credits, and utilizing the Rewards program to maximize savings and ensure compliance for corporate expense management.

A comprehensive guide and implementation pattern for handling common errors when working with the Runway AI platform. This skill provides Python SDK examples for tasks like image-to-video generation, along with structured solutions for API issues such as 'Unauthorized' (401) or 'Insufficient credits' (402), ensuring smooth and reliable creative AI workflows.

This skill provides implementation patterns and an SDK pattern for utilizing the RunwayML API. It allows users to perform advanced video generation, image-to-video tasks, and creative AI workflows directly within their code. Use cases include generating cinematic content, editing media, and managing API credits for complex creative projects.