performance

name	performance
description	Diagnose and improve runtime performance including N+1 queries, slow queries, caching, latency, memory, throughput, and resource efficiency using framework-agnostic principles.
metadata	{"internal":true}

Performance

Use this skill when work involves latency, throughput, resource usage, query efficiency, rendering cost, memory pressure, or scaling bottlenecks.

This skill is technology agnostic.

Measure First

Do not optimize solely from intuition.

Identify:

• the slow operation
• current baseline
• dominant cost
• expected improvement
• acceptable tradeoffs

Use measurements appropriate to the system.

Common Bottlenecks

Investigate relevant:

• repeated database queries
• N+1 access
• unnecessary network calls
• repeated computation
• inefficient algorithms
• excessive serialization
• large payloads
• blocking I/O
• unnecessary rendering
• memory growth
• contention
• cache misses
• excessive file operations

Do not assume the database is always the bottleneck.

Database Performance

Consider:

• query count
• query plans
• indexes
• join behavior
• selected columns
• pagination
• batch operations
• eager/bulk loading
• connection usage

Add indexes based on actual query patterns.

Caching

Cache when:

• computation or retrieval is meaningfully expensive
• reuse is likely
• consistency requirements are understood

Define:

• cache key
• lifetime
• invalidation
• ownership
• failure behavior

Do not add caching merely to hide an inefficient design without understanding correctness implications.

Memory

Avoid loading unbounded datasets into memory.

Prefer:

• streaming
• chunking
• pagination
• iterators
• bounded batches

when processing large data.

Concurrency

Parallelism can improve throughput but may increase:

• contention
• memory usage
• rate-limit pressure
• database load
• ordering complexity

Use bounded concurrency.

Verification

Compare before and after.

Verify:

• functional behavior remains correct
• measured metric improves
• resource usage remains acceptable
• no significant regression is introduced elsewhere

Performance work without measurement should be treated as a hypothesis, not a proven optimization.

Framework Adaptation

Use native profiling, caching, ORM, worker, and runtime mechanisms from the detected project stack.

Do not invent framework-specific APIs.