Skill UI

A comprehensive guide to optimizing context window usage within AI coding environments like Cursor. Learn how to strategically use @-mentions, manage context pills, and leverage different context sources (codebase, documentation, web) to prevent context overflow and ensure the AI generates highly accurate, relevant, and context-aware code suggestions and answers for complex development tasks.

A comprehensive guide for integrating and managing VS Code extensions within the Cursor IDE environment. This resource details the transition from the Microsoft Marketplace to the Open VSX Registry, covering installation methods (in-app, VSIX, CLI), conflict resolution with advanced AI features (e.g., Copilot, TabNine), and best practices for ensuring optimal performance and recommended extension stacks for various languages like Python, JavaScript, and Go.

A comprehensive guide to diagnosing and resolving common codebase indexing issues in Cursor IDE. Covers problems like stuck indexing, empty search results (@Codebase), stale data, and performance bottlenecks in large monorepos. Includes steps for cache clearing, configuration management, and optimizing resource limits.

A comprehensive guide for diagnosing and fixing common integration errors with Customer.io. It covers critical topics such as API status codes (400, 401, 429), authentication failures, incorrect timestamp formatting, and best practices for event tracking and transactional message delivery. Use this resource when troubleshooting campaign failures or API calls failing.

A protocol that provides LLM agents with persistent structural memory of a codebase. It maps the project as a directed graph, tracking not only dependencies (what imports what) but also the 'reasons' (why it connects). This allows agents to understand context, perform impact analysis, and navigate large repositories without loading the entire source code into the context window.

Use Declarative Automation Bundles (DABs) to manage and deploy Databricks assets, including jobs, DLT pipelines, and ML models, using an Infrastructure-as-Code approach. This skill allows defining resources and deployment targets (dev, staging, prod) in a single YAML file, enabling robust CI/CD practices and controlled promotion of changes across environments.

A comprehensive guide to setting up a fast, isolated local development loop for data engineering projects using Databricks Connect v2, Asset Bundles, and standard IDEs (like VS Code). This workflow allows developers to run PySpark code locally for debugging and unit testing, while managing resource deployment and ensuring consistency across development, staging, and production environments.

A comprehensive guide detailing best practices for building reliable, fault-tolerant Python applications utilizing DBOS durable workflows. This resource is essential when integrating DBOS into existing Python codebases, defining complex workflows and steps, managing concurrency via queues, or implementing robust workflow communication patterns.

Personalized reports that analyze recent Claude Code chats to surface recurring challenges, highlight learning gaps, curate HackerNews resources, and deliver actionable development insights directly to your Slack DMs for targeted growth.

This resource provides a minimal working example for implementing a complete digital document signing workflow using the Documenso SDK. It comprehensively guides users through creating a document, uploading a PDF file, adding designated recipients, placing specific signature fields, and finally triggering the signing process via code examples (TypeScript, Python) or REST API calls. Use this when integrating document signing into new applications or testing core document management capabilities.

A comprehensive guide for migrating from Documenso's legacy v1 API (document-centric) to the modern, recommended v2 API (envelope-based). This resource covers SDK upgrades for TypeScript and Python, providing code migration examples, best practices for implementing feature flags for gradual rollout, and steps for self-hosted container version upgrades.

A comprehensive guide and code implementation for setting up observability, metrics, and alerting for Exa search integrations. This skill tracks crucial KPIs such as search latency (P50/P95), error rates, result usage, and cache hit ratios. It is essential for monitoring search quality, debugging performance bottlenecks, and managing API resource usage in production environments.