PDD-CLI Bug: Generates Analytics Modules With Incomplete Metric Calculations

## PDD-CLI Bug: Generates Analytics Modules With Incomplete Metric Calculations

PDD-CLI creates analytics module structure with some metrics calculated, but doesn't implement all derived metrics or aggregations. Analytics endpoints return partial data.

**Why this matters:** Analytics dashboards show incomplete data, missing key metrics that should be calculated from available data.

## Concrete Example

For email campaign analytics:

```python
# PDD generated (INCOMPLETE):
def get_email_analytics(campaign_id: str) -> dict:
    """Calculate email analytics."""
    emails = get_campaign_emails(campaign_id)
    
    return {
        'total_sent': len(emails),
        'total_delivered': sum(1 for e in emails if e.delivered),
        'total_opened': sum(1 for e in emails if e.opened),
        'total_clicked': sum(1 for e in emails if e.clicked),
        # Missing: open_rate, click_rate, click_through_rate!
    }
```

**What went wrong:** PDD calculated raw counts but didn't implement derived percentages/rates that analytics dashboards typically need.

**Impact:** Dashboard shows "150 opened" but not "30% open rate" - users have to calculate manually.

## Why PDD Makes This Mistake

PDD-CLI currently:
- Implements direct metrics (counts, sums)
- Doesn't derive secondary metrics (rates, percentages, averages)
- Stops at basic aggregation

But it should:
1. Calculate all standard metrics for domain
2. Derive percentages and rates from counts
3. Handle edge cases (division by zero)

## How to Prevent This in PDD-CLI

**What PDD should do differently:**

1. **Implement complete metric calculations:**
   ```python
   def get_email_analytics(campaign_id: str) -> dict:
       emails = get_campaign_emails(campaign_id)
       
       total_sent = len(emails)
       total_delivered = sum(1 for e in emails if e.delivered)
       total_opened = sum(1 for e in emails if e.opened)
       total_clicked = sum(1 for e in emails if e.clicked)
       
       return {
           'total_sent': total_sent,
           'total_delivered': total_delivered,
           'total_opened': total_opened,
           'total_clicked': total_clicked,
           # Derived metrics
           'open_rate': (total_opened / total_delivered * 100) if total_delivered > 0 else 0,
           'click_rate': (total_clicked / total_opened * 100) if total_opened > 0 else 0,
           'click_through_rate': (total_clicked / total_delivered * 100) if total_delivered > 0 else 0,
       }
   ```

2. **Learn domain-specific metrics:** Know that email analytics needs rates, conversion funnels need drop-off rates, etc.

3. **Generate complete analytics specs:** Document all metrics that should be calculated.

**Example improvement:**
```
Current: "Calculate email analytics"
       → Generate counts (sent, opened, clicked)
       → Missing rates and percentages
       → Incomplete dashboard

Improved: "Calculate email analytics"
        → Generate counts
        → Generate derived rates (open_rate, click_rate, etc.)
        → Handle edge cases (division by zero)
        → Complete analytics
```

## Severity

**P2 - Medium Priority**

- **Frequency:** Low - only affects analytics features
- **Impact:** Medium - analytics incomplete, manual calculation needed
- **Detectability:** Medium - missing metrics obvious to domain experts
- **Prevention cost:** Low - add derived calculations

## Category

`incomplete-implementation`



**For Contributors:** Discovered when email analytics lacked `open_rate` and `click_rate` calculations, manually added in commit `34a651d5`.


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PDD-CLI Bug: Generates Analytics Modules With Incomplete Metric Calculations #588