Resume work from handoff document with context analysis and validation

Planning agent that creates implementation plans and handoffs from conversation context

Setup Ralph autonomous coding loop (external fresh-context pattern)

Draft professional emails for various contexts including business, technical,

TDD workflow for migrations - orchestrate agents, zero main context growth

Compress and simplify prompts to preserve meaning while reducing use of context

Guide for creating high-quality MCP (Model Context Protocol) servers

Generate an optimized AGENTS.md file after analyzing the directory/codebase for context.

Process large contexts using RLM (Recursive Language Model) patterns - chunking, filtering, recursive sub-calls

Knowledge graph-based code understanding with semantic search and 80% token reduction through intelligent context retrieval.

Detect and prevent state-visibility violations across execution contexts within a single transaction.

Intelligent code review dispatcher - automatically selects best reviewer based on context and preferences

Update docs and context for OpenSpec changes. Use when: saving session state, refreshing docs after implementation, or syncing change status.

Senior Architect for @google/genai v1.35.0+. Specialist in Structured Intelligence, Context Caching, and Agentic Orchestration in 2026.

Guide for AI Agents and LLM development skills including RAG, multi-agent systems, prompt engineering, memory systems, and context engineering.

Strategic compaction suggestion framework that monitors session complexity and suggests context compaction at optimal logical boundaries rather than arbitrary thresholds.

Feature-first init: create or reuse worktree/branch and seed per-feature context. Git-aware and idempotent.

Project setup. Explore the codebase, ask about strategy and aims, write persistent context to AGENTS.md. Run when starting or when aims shift.

Master of LLM Economic Orchestration, specialized in Google GenAI (Gemini 3), Context Caching, and High-Fidelity Token Engineering.

Build evaluation frameworks for agent systems. Use when testing agent performance, validating context engineering choices, or measuring improvements over time.