Skill UI

This skill provides advanced techniques to significantly reduce API costs when using Firecrawl for web scraping. It covers best practices such as setting crawl limits, utilizing batch scraping for known URLs, implementing local caching, and monitoring credit usage. Learn how to efficiently scrape large sites while managing budgets and minimizing unexpected billing spikes.

A comprehensive reference guide for developers to debug and resolve common errors encountered when integrating with the Gamma API. Covers specific error codes such as authentication failures (401/403), rate limit issues (429), content generation failures, and timeouts. Provides detailed solutions, best practices, and code snippets for robust error handling and reliable API usage.

This guide provides comprehensive strategies for optimizing API usage and managing expenditure when interacting with AI generation platforms like Gamma. It details implementing credit tracking systems to monitor consumption, employs cost-saving techniques (such as selecting lower-tier images or using templates), and demonstrates setting up proactive budget alerts to ensure spending remains within budget.

This skill provides a robust framework for implementing Role-Based Access Control (RBAC) when integrating with Gamma API in enterprise or multi-tenant environments. Since Gamma's API key is workspace-level, this solution enforces granular, per-user permissions (Guest, Viewer, Editor, Admin) at the application layer. Key components include authorization middleware, multi-tenant isolation logic, usage quota management, and detailed audit logging, ensuring system security and compliance in large-scale deployments.

This guide provides comprehensive techniques for managing API rate limits and ensuring reliable, high-volume API usage with Gamma. It covers methods such as reading rate limit headers, implementing exponential backoff for automatic retries, and building robust request queuing systems to handle throttling gracefully.

This skill guide is essential for building advanced applications using Gemini and Gemma 4 hosted models. It covers working with multimodal content (text, images, audio, video), implementing complex features like function calling and structured output. It provides up-to-date SDK usage examples for Python, JavaScript, Go, and Java, ensuring developers use the latest, recommended API standards.

Transforms OpenAPI specifications into comprehensive, interactive documentation sites. This skill generates runnable code examples (cURL, Python, JS, Go), detailed authentication guides, error references, and supports versioning. It is crucial for building professional developer portals that guide users through API usage seamlessly.

This skill provides comprehensive guidelines for monitoring Granola usage, tracking team meeting patterns, and building detailed analytics dashboards. It guides users in defining critical metrics (e.g., adoption rate, efficiency score) and establishing robust data pipelines. Users can stream meeting metadata from Granola to data warehouses like BigQuery, enabling deep, customizable reporting and automated weekly insights via services like Zapier and Slack.

This guide details the usage limits, quotas, and rate limits across Granola's various plans (Basic, Business, Enterprise). It helps users understand the differences between tiers, the constraints on meetings, meeting history, and the Enterprise API, ensuring users can select the appropriate plan to avoid service interruptions and optimize API usage.

A comprehensive guide to optimizing Groq API usage and managing inference costs. Learn techniques such as smart model routing (selecting smaller models for simple tasks), minimizing prompt tokens, batching requests to reduce overhead, and implementing caching for deterministic calls. This guide helps developers achieve significant cost savings and improve system efficiency when handling high-volume AI workloads.

A comprehensive, compliant wrapper for integrating with the Groq API. This module automatically sanitizes input prompts and filters model responses to redact sensitive PII (emails, phone numbers, SSN, etc.). It also tracks detailed token usage and generates robust audit logs, ensuring data privacy and regulatory compliance (GDPR, etc.) in enterprise AI applications.

This guide details how to implement robust, multi-layered Role-Based Access Control (RBAC) for managing LLM API calls to Groq in an enterprise setting. It covers best practices for API key scoping, application-level authorization (model selection, token limits), rate limiting, and detailed spending control mechanisms, ensuring secure and cost-effective usage across multiple teams.