Skill UI

This guide details how to implement comprehensive observability for various Adobe API integrations (e.g., Firefly, PDF Services). It covers the four pillars of observability: structured metrics using Prometheus, distributed tracing via OpenTelemetry, structured JSON logging, and defining critical alert rules. This ensures deep visibility into API performance, latency, and error rates for robust production monitoring.

Implements automated, multi-layered policy enforcement and guardrails for Adobe integrations. This skill provides crucial security checks, including detecting sensitive credentials (e.g., p8_ secrets), pre-screening content for services like Firefly (blocking trademarks or explicit material), and enforcing usage quotas for PDF Services. It is essential for maintaining secure and compliant CI/CD pipelines.

A comprehensive, step-by-step checklist for safely deploying Adobe API integrations (including Firefly, PDF Services, and I/O Events) to a production environment. It covers prerequisite checks, credential security, health monitoring, gradual canary rollouts, error handling, and immediate rollback procedures to ensure maximum system stability and reliability.

A comprehensive guide to production-ready patterns for integrating with Adobe services (Firefly, PDF, etc.). This includes robust authentication with token caching, typed API wrappers with advanced error classification, exponential backoff retry mechanisms, and job polling for asynchronous tasks. Essential for building reliable and maintainable Adobe API integrations in TypeScript or Python.

A comprehensive guide for developers tackling critical Adobe API upgrades. It covers major breaking changes and migration paths, including transitioning from JWT to OAuth Server-to-Server authentication, updating the PDF Services SDK from v3 to v4 (job-based API), and migrating Photoshop endpoints from v1 to v2. Essential for ensuring stable integration with Adobe Creative Cloud services.

This skill automates the generation of formal drawing descriptions and comprehensive reference numeral indexes for patent applications. It processes user-provided technical diagrams (PNG, JPG, PDF), identifies components, maps connections, and assigns standardized reference numerals across multiple figures. It ensures that all technical descriptions are consistent, legally compliant, and cross-referenced accurately against the claims, streamlining the patent drafting process.

This skill provides a comprehensive workflow for managing Lucidchart documents and diagrams using the REST API. Users can programmatically execute the full lifecycle: creating new documents, adding complex shapes and connectors via the Standard Import format, modifying existing content, and exporting the final diagram into high-resolution formats like PNG, PDF, or SVG. Ideal for automated diagram generation and content lifecycle management.

Designs a scalable, version-controlled integration layer for the Lucidchart platform. This architecture tracks every shape mutation for diffing and rollback, implements real-time collaboration event consumption, and manages asynchronous export pipelines (PNG/SVG/PDF) using dedicated worker pools and caching strategies. Ideal for developing robust SaaS integrations requiring rigorous data synchronization.

The Desktop Commander MCP grants agents deep reach across the user's entire operating environment, extending far beyond the typical IDE sandbox. Key capabilities include maintaining persistent shell sessions, managing long-running background processes, accessing arbitrary filesystems, and natively handling structured data formats (Excel, PDF, DOCX). It also enables remote operations via SSH and large-scale content search, making it ideal for complex, multi-turn development, DevOps, and data analysis workflows.

This skill guides the design of robust, production-grade data extraction pipelines, moving beyond brittle one-off scripts. It supports three modes: API-driven web scraping (Firecrawl), traditional local Python extraction (PDF, CSV), and hybrid workflows. Key features include intelligent routing, mandatory data validation, secure key management, and adherence to scraping best practices.

This meta-skill automates the complex process of modernizing legacy PDF documents (e.g., historical contracts, scanned manuals, legal documents). It follows a structured four-step pipeline: structural extraction, natural-language rewriting of problem pages, generating an audit summary, and finally re-merging the content into a single, refined PDF. This ensures content is modernized while maintaining fidelity to the original meaning, providing a human review summary before finalization.

nano-pdf is a robust command-line interface (CLI) tool designed to modify PDF documents. Instead of requiring complex PDF editing syntax, users can provide natural language instructions (e.g., 'Change the title to X and fix Y') to make precise edits to specific pages of a PDF. This drastically simplifies the content modification process for technical users and automates complex document handling tasks.