/cf-optimize
Structured optimization with before/after measurement.
The /cf-optimize skill systematically improves performance by measuring baseline metrics, analyzing bottlenecks, implementing optimizations, and comparing results.
Usage
/cf-optimize [target]
Workflow
- Baseline Measurement — Profile code to establish current performance metrics
- Bottleneck Analysis — Identify the slowest operations and root causes
- Optimization — Implement improvements (algorithm, caching, indexing, etc.)
- Verify Results — Measure performance after changes
- Compare & Report — Show before/after with percentage improvement
Examples
/cf-optimize getUserById query
/cf-optimize search endpoint response time
/cf-optimize database migration script
What Gets Measured
- Execution Time — Wall-clock and CPU time
- Memory Usage — Peak and average memory consumption
- Database Queries — Query count and slow query analysis
- Network I/O — Request/response sizes and latency
- Throughput — Requests per second (for endpoints)
Output Example
BASELINE:
getUserById: 250ms avg, 15 DB queries per call
OPTIMIZATION:
- Added query result caching (Redis)
- Optimized N+1 query in related data fetch
- Added database index on user_id
AFTER:
getUserById: 45ms avg, 1 DB query per call
Improvement: 82% faster, 93% fewer queries
When to Use
- Performance bottlenecks identified by users
- Database queries timing out
- Page load times slowing growth
- API endpoints hitting rate limits
- Memory leaks in long-running processes