Skill UI

This comprehensive guide details advanced strategies for optimizing interactions with the Gamma API. It covers critical best practices including implementing smart polling with adaptive backoff, caching static resources (themes, folders), executing parallel batch generations, and minimizing generation latency by tuning content parameters. Essential for developers building robust and high-performance Gamma integrations.

A comprehensive guide providing reference architectural patterns for building scalable, maintainable, and robust enterprise integrations involving Gamma services. It details three patterns—Basic, Service Layer, and Event-Driven—covering use cases from simple prototypes to high-volume, microservices-based systems, guiding system designers and architects on best practices.

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.

This guide demonstrates how to build a resilient, event-driven architecture for Gamma API integrations when native webhooks are unavailable. It utilizes a poll-based pattern, creating synthetic application-level events (start, completed, failed) by wrapping polling logic within an EventEmitter or message queue. Ideal for building background workers that reliably track and react to the full lifecycle of content generation.

Automates Gan AI operations through Composio’s Rube MCP integration, guiding users to search schemas, verify active connections, and execute workflows with schema-compliant arguments and session reuse.

Gastown is a robust multi-agent orchestration system designed for Claude Code. It enables the simultaneous execution of multiple AI agents on complex projects. It manages the entire development lifecycle, from setting up workspaces and tracking work items (beads) to managing agent lifecycles (polecats/crew) and merging final code (Refinery). Use it when coordinating complex, parallel AI tasks.

Guides building production-ready serverless apps on GCP with Cloud Run services and Functions, covering containerized APIs, event-driven Pub/Sub workflows, cold-start tuning, and deployment automation.

Generates complete, production-ready Google Cloud Platform (GCP) code examples and infrastructure templates. It spans various modern AI patterns, including ADK agents, Genkit RAG flows, and multimodal analysis using Vertex AI and Gemini. The output includes runnable code, deployment configuration (Terraform/IaC), security best practices (IAM, VPC-SC), and monitoring setup, ensuring enterprise-grade reliability and cost optimization.

Provides automated guidance for Google Cloud Storage lifecycle policy scenarios, including pattern recommendations, production-ready configurations, and best practices for compute, storage, BigQuery, Vertex AI, and other GCP-specific services.

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.

Automates compliance and security audit reporting for standards such as PCI DSS, HIPAA, SOC 2, and ISO 27001 by using the compliance-report-generator plugin to collect details, format documentation, and streamline regulatory proof.

Generates conventional commit messages using AI by analyzing staged Git changes and recommending standardized text for features or fixes, helping teams keep commit history consistent during development.