Smart Diff Analysis

Intelligent analysis of code changes with automatic chunking for large diffs and context-aware processing for better AI understanding.

Intelligent Change Analysis

Advanced diff processing that understands code structure and context, not just line changes. Perfect for generating meaningful commit messages from complex changes.

✓ Context-aware diff parsing
✓ Semantic change detection
✓ Binary file handling
✓ Language-specific processing

Diff analysis process:

Parse git diff output

Identify change types

Extract semantic context

Generate AI prompts

Automatic Diff Chunking

Smart Size Management

Large changes are automatically split into manageable chunks that fit within AI token limits while preserving logical context.

• Configurable chunk size limits
• Context-preserving splits
• Function boundary awareness
• File grouping logic

Intelligent Merging

Chunk results are intelligently merged back together, deduplicating similar points and creating coherent commit messages.

# Chunking configuration

ai:

max_prompt_chars: 90000

chunk_size: 28000

fallbacks:

minimal_diff: true

Advanced Change Detection

🔍

Semantic Analysis

Understands what changes mean, not just what lines changed

📁

File Type Awareness

Different processing for code, config, docs, and binary files

🎯

Impact Assessment

Identifies high-impact changes and breaking modifications

Binary & Large File Handling

📦 Binary File Detection

Automatically detects binary files and handles them appropriately without trying to analyze their content.

• Git numstat analysis
• File extension patterns
• Content-based detection
• Git LFS recommendations

⚠️ Size Warnings

Warns about large files that might cause issues and suggests alternatives like Git LFS.

• Configurable size thresholds
• Pre-commit warnings
• Git LFS suggestions
• Repository health checks

Intelligent Fallback Modes

When AI Fails

Multiple fallback strategies ensure you always get useful commit messages, even when AI services are unavailable.

• File-based change inference
• Statistical analysis mode
• Template-based generation
• Manual override options

Minimal Diff Mode

When changes are too large for AI processing, switches to a minimal diff mode that focuses on key changes.

# Fallback configuration

fallbacks:

minimal_diff: true

stats_mode: true

offline_template:

subject: "Update changes"

Optimized Performance

Efficient diff processing that scales from small tweaks to massive refactors without compromising speed or accuracy.

Speed Optimizations

• Parallel chunk processing
• Efficient diff parsing
• Cached analysis results
• Incremental processing

Memory Management

• Streaming diff processing
• Garbage collection
• Memory-efficient chunking
• Resource cleanup

Scalability

• Handles massive repositories
• Adaptive processing limits
• Timeout management
• Graceful degradation