Phase 2+3: Deep AI context + acorn sync

[SilasFu]

Summary

Complete the strategic roadmap (Phase 2 + Phase 3) for the AI coding environment optimizer.

Phase 2: Deep AI Context Generation

• 15+ analysis dimensions: import style, module system, naming convention, state management, styling approach, API style, architecture pattern, directory purposes
• analysis/ast_lite.py: regex-based code analysis engine (no heavy AST parser needed)
• Rich .cursorrules/CLAUDE.md/copilot-instructions.md: now include project structure, API routes, tech stack details, architecture patterns

Phase 3: acorn sync

• Drift detection: compares current project state vs generated AI context files
• Auto-regeneration: updates stale files on confirmation
• acorn sync --sync-hook: installs a pre-commit git hook to keep AI context fresh

Stats

• 609 tests, 87% coverage
• Version bump 0.2.0 → 0.3.0
• 12 files changed, +1066 / -48 lines

Usage

acorn sync                    # Check and update stale AI context
acorn sync --sync-hook        # Install pre-commit hook
acorn sync --dry-run          # Preview changes