Outline Load Profile

Map the load characteristics of a component or system to understand its scaling behavior.

Arguments: $ARGUMENTS

Workflow

Step 1: Identify the Component

Read the target component from

$ARGUMENTS

. Explore its:

• Entry points (API endpoints, CLI commands, event handlers, scheduled jobs)
• Data stores it reads from and writes to
• External service calls

Step 2: Map Request Flow

For each entry point, trace the request path:

1. Ingress: How does work arrive? (HTTP, queue, cron, user action)
2. Processing: What computation happens? (CPU-bound, I/O-bound, memory-bound)
3. Egress: Where do results go? (response, database write, file output, notification)

Step 3: Estimate Load Dimensions

For each flow, estimate:

Dimension	Current	10x	100x
Requests/sec
Data per request
Total storage
Concurrent connections
Memory per request

Fill in what can be determined from code. Mark unknowns as

?

.

Step 4: Identify Bottlenecks

Look for:

• Single-threaded paths: Synchronous processing that blocks
• Unbounded collections: Arrays/lists that grow with input size
• N+1 queries: Database/API calls inside loops
• Global state: Shared mutable state across requests
• Missing pagination: Queries without LIMIT/OFFSET
• Large file reads: Reading entire files into memory

Step 5: Output the Load Profile

## Load Profile: [Component]

**Entry Points**: [count] ([list])
**Processing Type**: [CPU-bound | I/O-bound | Memory-bound | Mixed]

**Current Load Estimate**:
[table from Step 3]

**Bottlenecks Identified**:
1. [file:line] — [description]
2. [file:line] — [description]

**Scaling Risks**:
- [risk 1]
- [risk 2]

**Recommendation**: [scale-ready | needs-work | redesign-required]

This feeds into

/scale-review:evaluate

for detailed analysis.