Search Skills

Designs AI-assisted learning experiences using the Three Roles Framework (Teacher/Student/Co-Worker) for teaching AI-driven development workflows and spec-first collaboration.

Generates measurable learning outcomes using Bloom's taxonomy and CEFR levels, ensuring specificity and testability for curriculum development.

Configures OAuth 2.1 and OIDC authentication with Better Auth MCP for centralized SSO, Next.js clients, and token management.

Creates educational illustrations and diagrams using Gemini AI via browser automation with quality control, specifically for technical content creation.

Builds AI agents with Google's ADK, featuring Gemini integration, multi-agent workflows, and Vertex AI deployment.

Guides developers in building ChatGPT custom applications with interactive widgets, MCP server setup, and response metadata using the Apps SDK and FastMCP.

Manages Nx monorepo workspaces, including dependency analysis, affected command execution, code generation, and build optimization for AI-native development.

Plans and structures educational books using cognitive load management and pedagogical best practices for progressive learning.

Provides AI-powered repository analysis and RAG-based Q&A for open-source codebases on GitHub, GitLab, and Bitbucket.

Automates extraction and routing of session learnings to organizational knowledge systems, transforming one-time fixes into permanent codebase improvements across multiple files.

Reviews technical writing to enhance accessibility, reduce jargon, and eliminate gatekeeping language for broader audience clarity.

Generates rigorous MIT PhD-level qualifying exams from Markdown/Obsidian notes for educational assessment and study purposes.

Validates Claude skills against production-level quality criteria, providing scores and recommendations for structure, documentation, and technical robustness.

Automates generation of MIT-standard certification exams in DOCX format for chapters or parts, saving to assessments directory.

Builds AI agents using OpenAI's Agents SDK and LiteLLM for multi-model support, including tool implementation and agent handoffs.

Provides a structured debugging methodology emphasizing root cause analysis, pattern recognition, and hypothesis testing to resolve technical issues efficiently.

Optimizes AI agent context capacity to overcome limitations, reduce costs, and improve performance in long-running systems.

Evaluates UI components against UX best practices using a 3D framework (Position, Visual Weight, Spacing) aligned with Nielsen heuristics and Balsamiq standards.

Builds AI chat interfaces with custom backends, authentication, and context injection for seamless integration with AI agents.

Automates browser interactions including navigation, form filling, element clicking, and data extraction for web scraping and UI testing.

Deploys and manages Kubernetes clusters across multiple cloud providers, covering cluster setup, networking, and cost optimization.

Designs progressive learning sequences using Bloom's taxonomy and CEFR levels to build foundational knowledge step-by-step while managing cognitive load.

Configures production traffic engineering for Kubernetes with Envoy Gateway, Gateway API, and KEDA for ingress, routing, rate limiting, and LLM traffic management.

Builds persistent memory systems for AI agents using Mem0, claude-mem, or custom solutions for conversation memory, preferences, and contextual recall.