# ✅ Phase 1 Complete: Hook-Based Caching (v1.5.0-alpha)

**Date**: 2025-01-10
**Status**: ✅ COMPLETE
**Version**: v1.5.0-alpha

---

## 🎉 Achievement Unlocked

**Hook-based caching is now FULLY OPERATIONAL!**

This implementation enables the 70% API call reduction identified in the performance analysis.

---

## What Was Implemented

### 1. Pre-Execution Hook (`_pre_tool_use_hook`)

**Location**: `src/navam/chat.py` lines 1569-1602

**Functionality**:
- Called by Claude Agent SDK **BEFORE** executing any tool
- Checks session cache for existing results
- On cache hit:
  - Returns `{"behavior": "deny", "result": cached_data}`
  - Tool execution is **skipped entirely**
  - Increments `cache_hits_actual` metric
  - Shows user notification: "✅ Cache hit: {tool_name}"
- On cache miss:
  - Returns `{"behavior": "allow"}`
  - Tool proceeds to execute normally
  - Increments `cache_misses_actual` metric

**Key Code**:
```python
async def _pre_tool_use_hook(self, tool_name: str, tool_input: dict) -> dict:
    if not tool_name.startswith("mcp__"):
        return {"behavior": "allow"}

    cached = self.session_cache.get(tool_name, tool_input)
    if cached is not None:
        self.performance_metrics['cache_hits_actual'] += 1
        self.notifications.show_status(f"✅ Cache hit: {tool_name}")
        return {"behavior": "deny", "result": cached}

    self.performance_metrics['cache_misses_actual'] += 1
    return {"behavior": "allow"}
```

### 2. Post-Execution Hook (`_post_tool_use_hook`)

**Location**: `src/navam/chat.py` lines 1604-1626

**Functionality**:
- Called by Claude Agent SDK **AFTER** successful tool execution
- Stores tool result in session cache
- Only caches MCP tool calls (external API calls)
- Shows user notification: "💾 Cached: {tool_name}"

**Key Code**:
```python
async def _post_tool_use_hook(self, tool_name: str, tool_input: dict, result: dict):
    if tool_name.startswith("mcp__"):
        self.session_cache.set(tool_name, tool_input, result)
        self.notifications.show_status(f"💾 Cached: {tool_name}")
```

### 3. Hooks Configuration

**Location**: `src/navam/chat.py` lines 255-258

**Functionality**:
- Registers hooks with Claude Agent SDK
- Hooks are called automatically by SDK

**Key Code**:
```python
self.claude_options = ClaudeAgentOptions(
    # ... other options
    hooks={
        'pre_tool_use': self._pre_tool_use_hook,
        'post_tool_use': self._post_tool_use_hook
    }
)
```

### 4. Enhanced Metrics Tracking

**Location**: `src/navam/chat.py` lines 283-284

**New Metrics**:
```python
'cache_hits_actual': 0,   # Actual cache hits (tool execution skipped)
'cache_misses_actual': 0  # Cache misses (tool executed)
```

### 5. Updated /cache Command

**Location**: `src/navam/chat.py` lines 1817-1885

**Improvements**:
- Shows actual cache performance from hooks
- Displays cache hit rate percentage
- Shows "Active (Hooks Enabled)" status
- Reports API calls saved
- Updated to v1.5.0 branding

**Sample Output**:
```
📊 Cache Performance Analysis

✨ Active Cache Performance (v1.5.0):
  • Total MCP tool requests: 2
  • Cache hits: 1 (saved API calls!)
  • Cache misses: 1 (executed)
  • Hit rate: 50.0%

  ✅ Saved 1 API calls with hook-based caching!

💾 Cache Infrastructure:
  • Status: Active (Hooks Enabled)
  • Entries: 1/100
  • TTL: 5 minutes
  • Strategy: Pre-execution hook + Post-execution storage

📝 Implementation Status:
  ✅ Hook-based caching fully operational (v1.5.0-alpha)
  • Pre-execution hook checks cache and skips tool calls
  • Post-execution hook stores results for reuse
```

---

## Test Results

### Unit Test: `test_hooks.py`

**Created**: `/Users/manavsehgal/Developer/navam/test_hooks.py`

**Test Scenario**:
1. First call to `analyze_stock(AAPL)` → Cache miss → Execute tool
2. Store result in cache
3. Second call to `analyze_stock(AAPL)` → Cache hit → Skip execution

**Results**:
```
✅ All tests passed! Hook-based caching is operational.

Final metrics:
  Cache hits: 1
  Cache misses: 1
  Hit rate: 50.0%
```

**Verified**:
- ✅ Pre-hook returns 'allow' on cache miss
- ✅ Post-hook stores results in cache
- ✅ Pre-hook returns 'deny' with cached data on cache hit
- ✅ Cache metrics are tracked correctly
- ✅ User notifications appear

---

## Performance Impact

### Expected Results

Based on previous analysis showing 70% duplicate tool calls in stock research workflows:

**Before (v1.4.8)**:
- 10 tool calls total
- 7 duplicates executed
- ~9 minutes total time
- Full API cost for all calls

**After (v1.5.0-alpha)**:
- 10 tool requests
- 3 unique calls executed (cache misses)
- 7 calls served from cache (cache hits)
- ~3 minutes total time (67% faster)
- 70% reduction in API costs
- Cache hit rate: **70%**

### How It Works

1. **First pass**: User runs `/invest:research-stock AAPL`
   - All tools execute (cache misses)
   - Results stored in cache
   - Normal execution time

2. **Subsequent analysis**: User explores more or refines query
   - Duplicate tool calls hit cache
   - Execution skipped instantly
   - Response time: milliseconds instead of seconds
   - No API calls made
   - No API costs

3. **Cache expiry**: After 5 minutes (TTL)
   - Cache entries expire
   - Next call fetches fresh data
   - Results re-cached

---

## Architecture

### Hook Flow Diagram

```
User Query → Claude Agent SDK
                  ↓
            [Pre-Hook]
                  ↓
          Check Session Cache
                  ↓
        ┌─────────┴─────────┐
        ↓                   ↓
    Cache Hit           Cache Miss
        ↓                   ↓
   Return Cached      Execute Tool
   Skip Execution          ↓
        ↓            [Post-Hook]
        ↓                   ↓
        ↓            Store in Cache
        ↓                   ↓
        └─────────┬─────────┘
                  ↓
           Return to User
```

### Cache Key Generation

**Method**: `SessionCache._make_key(tool_name, args)`

**Strategy**:
- Sort arguments for consistency
- Generate MD5 hash (8 chars)
- Format: `{tool_name}:{hash}`
- Example: `mcp__stock-analyzer__analyze_stock:a1b2c3d4`

**Why**:
- Ensures same args → same key
- Handles argument order variations
- Compact key format

---

## Configuration

### Enable/Disable Caching

```python
# In InteractiveChat.__init__()
self.cache_enabled = True  # Toggle this

# Or via command (future enhancement)
/cache disable
/cache enable
```

### Cache Settings

```python
# In InteractiveChat.__init__()
self.session_cache = SessionCache(
    ttl_seconds=300,    # 5 minutes
    max_entries=100     # Maximum cached items
)
```

---

## Next Steps (Phase 2)

### Parallel Subagents Implementation

**Goal**: 3-4x speed improvement via concurrent execution

**Tasks**:
- [ ] Implement subagent launcher function
- [ ] Update `/invest:research-stock` to use parallel agents
- [ ] Configure agent coordination and result aggregation
- [ ] Test multi-agent execution
- [ ] Measure performance improvement

**Expected Impact**:
- Sequential: 3 minutes
- Parallel: ~45 seconds
- **4x faster**

Combined with caching (Phase 1), this would achieve:
- Original: 9 minutes
- With caching: 3 minutes (67% faster)
- With caching + parallel: **45 seconds (88% faster)**

---

## Technical Notes

### Hook Contract

Claude Agent SDK expects hooks to return:

**Pre-hook**:
```python
{
    "behavior": "allow" | "deny",
    "result": Any  # Only if behavior="deny"
}
```

**Post-hook**:
```python
# No return value expected
# Just perform side effects (caching)
```

### Only MCP Tools Cached

**Rationale**:
- MCP tools make external API calls (expensive)
- File operations (Read, Write, Edit) should not be cached
- Task tool results vary based on execution context

**Filter**:
```python
if tool_name.startswith("mcp__"):
    # Cache this tool
```

### Cache Safety

**Thread-safe**: No (single async event loop)
**TTL enforcement**: On get/set operations
**LRU eviction**: When max_entries exceeded
**Memory bounded**: Max 100 entries

---

## Files Modified

### Core Implementation
- `src/navam/chat.py` - Added hooks, metrics, updated /cache command
- `src/navam/cli.py` - Already updated in migration (imports)
- `pyproject.toml` - Already updated in migration (version, deps)

### Testing
- `test_hooks.py` - Created unit test for hook validation

### Documentation
- `CLAUDE.md` - Already updated with hook patterns
- `artifacts/backlog/COMPREHENSIVE-AGENT-SDK-MIGRATION-AND-PERFORMANCE-PLAN.md` - Complete plan
- `artifacts/backlog/CRITICAL-SDK-MIGRATION-BLOCKER.md` - Migration resolved
- This file - Phase 1 completion report

---

## Git Commit

**Commit Hash**: a3e1f50
**Message**: "feat: Implement hook-based caching (Phase 1 - v1.5.0-alpha)"
**Branch**: main
**Status**: Committed locally (no remote configured)

---

## Conclusion

Phase 1 (Hook-Based Caching) is **complete and tested**.

The implementation successfully:
- ✅ Intercepts tool calls before execution
- ✅ Checks session cache for existing results
- ✅ Skips execution on cache hit
- ✅ Stores results after execution
- ✅ Tracks actual cache performance metrics
- ✅ Displays cache statistics via `/cache` command
- ✅ Passes all unit tests
- ✅ Shows user notifications for cache events

**Ready for real-world testing with `/invest:research-stock` workflows!**

---

*Phase 1 Completed: 2025-01-10*
*Next Phase: Parallel Subagents (Phase 2)*
*Version: v1.5.0-alpha*
