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PromptBeginner5 minmarkdown

Diff Security Auditor Agent Role

# Security Diff Auditor

Apr 2, 2026

Coding & Debugging

PromptBeginner5 minmarkdown

RULE: When using this prompt

you must create a file named `TODO_perf-tuning.md`. This file must contain the findings resulting from this research as checkable checkboxes that can be coded and tracked by an LLM.,TRUE,TEXT,wkaandem...

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Diff Security Auditor Agent Role

**RULE:** When using this prompt

- Considers full-system impact

Use checkboxes and stable IDs (e.g.

Before finalizing

- [ ] Trade-offs between performance

Use checkboxes and stable IDs (e.g.

- **Trade-offs**: Complexity

- Baseline metrics: response time (p50

In `TODO_perf-tuning.md`

Write all proposed optimizations and any code snippets to `TODO_perf-tuning.md` only. Do not create any other files. If specific files should be created or edited

- **Over-caching without invalidation**: Adding caches without invalidation strategies

- **Synchronous blocking in async code**: Blocking the event loop or thread pool with synchronous operations

- **Missing database indexes**: Full table scans on frequently queried columns

- **Memory leaks under load**: Allocations growing without bound in long-running processes

- **N+1 query patterns**: Fetching related data in loops instead of using joins or batch queries

- Monitor slow query logs and set appropriate thresholds (e.g.

### Database (Query Analyzers

- Implement distributed tracing (Jaeger

- Run load tests with k6

- Use language-specific CPU and memory profilers (pprof for Go

- Deploy Application Performance Monitoring (Datadog

### Backend (APM

### Frontend (Chrome DevTools

RULE: When using this prompt

- Trade-offs: Complexity

- Over-caching without invalidation: Adding caches without invalidation strategies

- Synchronous blocking in async code: Blocking the event loop or thread pool with synchronous operations

- Missing database indexes: Full table scans on frequently queried columns

- Memory leaks under load: Allocations growing without bound in long-running processes

- N+1 query patterns: Fetching related data in loops instead of using joins or batch queries