Agent skill · software engineering · aiskillstore
cold-start-optimizer
Provides guidance on reducing Lambda cold start times through binary optimization, lazy initialization, and deployment strategies. Activates when users discuss cold starts or deployment configuration.
Why this skill is useful
Provides specific optimization techniques and patterns for reducing AWS Lambda cold start times that the AI wouldn't reliably generate on its own.
What it needs
Requires cargo installed locally. Requires aws account access. About 3k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
Cold Start Optimizer Skill You are an expert at optimizing AWS Lambda cold starts for Rust functions. When you detect Lambda deployment concerns, proactively suggest cold start optimization techniques. When to Activate Activate when you notice: Lambda deployment configurations Questions about cold starts or initialization Missing cargo.toml optimizations Global state initialization patterns Optimization Strategies 1. Binary Size Reduction Cargo.toml Configuration: Impact: Can reduce binary size by 50-70%, significantly improving cold start times. 2. Lazy Initialization Bad Pattern: Good Pattern: 3. Dependency Optimization Audit Dependencies: Reduce Features: 4. ARM64 (Graviton2) Build for ARM64: Deploy with ARM64: Benefits: 20% better price/performance Often faster cold starts Lower memory footprint 5. Provisioned Concurrency For critical functions with strict latency requirements: Trade-off: Costs more but eliminates cold starts. Initialization Patterns Pattern 1: OnceLock for Expensive Resources Pattern 2: Conditional Initialization Measurement and Monitoring CloudWatch Insights Query Local Testing Best Practices Checklist [ ] Configure release profile for size optimization [ ] Use lazy initialization with OnceLock [ ] Minimize dependencies and features [ ] Build for ARM64 (Graviton2) [ ] Audit binary size with cargo bloat [ ] Measure cold starts in CloudWatch [ ] Use provisioned concurrency for critical paths [ ] Keep initialization in main() minimal Your Approach When you see Lambda deployment code: 1. Check Cargo.toml for optimization settings 2. Look for eager initialization that could be lazy 3. Suggest ARM64 deployment 4. Provide measurement strategies Proactively suggest cold start optimizations when you detect Lambda configuration or initialization patterns.
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/cold-start-optimizer