Skill UI

This comprehensive 'Hello World' guide serves as a foundational tutorial for Framer development. It demonstrates key skills across the ecosystem, including building functional plugins (UI interaction), creating customizable code components with property controls, implementing dynamic code overrides for sophisticated animations, and interacting with the Framer Server API for headless site data management. Ideal for developers starting a new Framer integration or mastering core API patterns.

This guide details how to set up a robust, local development loop for Framer plugins and components. It covers hot-reloading using Vite, writing unit tests with Vitest, and integrating with the Framer Server API. This workflow enables developers to achieve fast iteration cycles, ensuring seamless development from concept to production-ready prototype within the Framer environment.

Provides a comprehensive reference architecture for building production-ready Framer integrations. This guide covers optimal project layout, including plugins, server API backend, CMS synchronization patterns, and advanced code components. Use it when designing new, complex Framer applications or establishing enterprise-level development standards.

This skill demonstrates how to build a robust, event-driven indexing system for Glean. It processes real-time webhooks received from various source systems (like GitHub, Notion, Confluence), handling events such as document indexing, permission changes, and search anomalies. The solution includes critical components like signature verification and idempotent message handling to ensure data consistency and reliability.

This guide details the recommended reference architecture and project structure for integrating with the Hex platform. It covers best practices for designing robust data pipelines, including components like orchestration layers (Airflow, Dagster), API clients, and standardized project layouts. Use this when starting new Hex integrations or reviewing complex data workflows.

This skill analyzes an existing codebase using domain context and architectural decisions to identify architectural friction and "deepening opportunities." It proposes refactored improvements to increase module depth, enhancing testability, improving maintainer locality, and making the codebase more navigable for AI tools. It focuses on transforming shallow modules into robust, deeply leveraged components.

Master advanced patterns for composing LangGraph subgraphs, which is essential for building robust, multi-agent systems like planner-executors or hierarchical teams. This skill addresses critical issues such as shared state contract propagation (P21) and callback scoping (P28). Learn to manage state across independent graph components using sophisticated dispatch patterns: compiled nodes, Send fan-out, and Command bubble-up.

This guide provides comprehensive strategies for minimizing operational costs within the MindTickle learning platform. It details cost drivers across various components, including seat licenses, content storage, quiz assessments, call recording analysis, and API integrations. Users can learn best practices for content deduplication, implementing incremental sync, setting proper retention policies, and optimizing resource usage to reduce unnecessary spend and improve overall platform efficiency for sales organizations.

This reference architecture details the design of a multi-tenant integration layer for the MindTickle sales enablement platform. It strictly enforces tenant data isolation across all components (database, cache, queue) to ensure that organizational data remains separate. The system manages user synchronization (via SCIM 2.0), tracks course progress, records quiz results, and aggregates team readiness reports, making it ideal for complex SaaS enterprise deployments.

This skill runs a comprehensive, sequenced pipeline (Patterns 1-5) to structurally analyze a monolithic codebase. It inventories components, detects domain duplication, resolves hierarchy issues, measures inter-module coupling, and groups components into candidate, domain-aligned services. It is essential for architects planning service extraction, providing actionable metrics and DDD insights before refactoring or splitting the application.

A comprehensive offensive checklist for assessing the security and robustness of AI and Large Language Model (LLM) applications. It covers advanced adversarial techniques such as prompt injection, jailbreaking, model extraction, data poisoning, and analyzing system vulnerabilities across components. Essential for red-teaming and security assessment.

Provides a comprehensive, production-ready standard 3-tier reference architecture for Oracle Cloud Infrastructure (OCI). The design covers essential components like VCN, public/private subnets, Internet Gateway, NAT Gateway, Service Gateway, and Autonomous Database. It includes deployment steps using Terraform and OCI SDK Python code, making it ideal for designing new cloud environments or migrating existing patterns from other major cloud providers.