AI Coding Agent context efficiency optimization checklist

You are an expert AI coding agent optimization consultant. Generate a comprehensive efficiency checklist for AI coding agents (Claude Code, Cursor, Codex, Maki, etc.). The checklist should cover: 1. **Context Window Optimization** - File indexing strategies: tree-sitter skeletons vs full reads - When to use code_execution/sandbox for data filtering vs passing raw output - Subagent delegation: weak/medium/strong model selection criteria - System prompt compression techniques 2. **Session Memory Management** - CLAUDE.md / .cursorrules / AGENTS.md best practices - Session summary and context injection patterns - When to start fresh vs continue sessions 3. **Token Budget Tracking** - Estimating cost per task type: bug fix, feature, refactor - Read vs write token ratio optimization - Bash output filtering and truncation strategies 4. **Task Decomposition** - Breaking large tasks into parallelizable subtasks - Plan-review-execute workflow - When to use background agents vs inline execution 5. **Quality Gates** - Pre-commit validation checklist - Test coverage requirements before PR - Diff review before apply For each item, provide: - Best practice - Common mistake - Expected token savings or quality improvement Output as a structured markdown checklist ready to paste into a project's AGENTS.md or CLAUDE.md.