/m10-performance
CRITICAL: Use for performance optimization. Triggers: performance, optimization, benchmark, profiling, flamegraph, criterion, slow, fast, allocation, cache, SIMD, make it faster, 性能优化, 基准测试
$ npx -y skills add zhanghandong/rust-skills --skill m10-performance --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/m10-performance
Context preview
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CRITICAL: Use for performance optimization. Triggers: performance, optimization, benchmark, profiling, flamegraph, criterion, slow, fast, allocation, cache, SIMD, make it faster, 性能优化, 基准测试
SKILL.md
m10-performance.SKILL.mdname: m10-performance
description: "CRITICAL: Use for performance optimization. Triggers: performance, optimization, benchmark, profiling, flamegraph, criterion, slow, fast, allocation, cache, SIMD, make it faster, 性能优化, 基准测试"
user-invocable: false
Performance Optimization
> **Layer 2: Design Choices**
Core Question
**What's the bottleneck, and is optimization worth it?**
Before optimizing:
- Have you measured? (Don't guess)
- What's the acceptable performance?
- Will optimization add complexity?
---
Performance Decision → Implementation
| Goal | Design Choice | Implementation | |------|---------------|----------------| | Reduce allocations | Pre-allocate, reuse | `with_capacity`, object pools | | Improve cache | Contiguous data | `Vec`, `SmallVec` | | Parallelize | Data parallelism | `rayon`, threads | | Avoid copies | Zero-copy | References, `Cow<T>` | | Reduce indirection | Inline data | `smallvec`, arrays |
---
Thinking Prompt
Before optimizing:
1. **Have you measured?**
- Profile first → flamegraph, perf
- Benchmark → criterion, cargo bench
- Identify actual hotspots
2. **What's the priority?**
- Algorithm (10x-1000x improvement)
- Data structure (2x-10x)
- Allocation (2x-5x)
- Cache (1.5x-3x)
3. **What's the trade-off?**
- Complexity vs speed
- Memory vs CPU
- Latency vs throughput
---
Trace Up ↑
To domain constraints (Layer 3):
"How fast does this need to be?"
↑ Ask: What's the performance SLA?
↑ Check: domain-* (latency requirements)
↑ Check: Business requirements (acceptable response time)| Question | Trace To | Ask | |----------|----------|-----| | Latency requirements | domain-* | What's acceptable response time? | | Throughput needs | domain-* | How many requests per second? | | Memory constraints | domain-* | What's the memory budget? |
---
Trace Down ↓
To implementation (Layer 1):
"Need to reduce allocations"
↓ m01-ownership: Use references, avoid clone
↓ m02-resource: Pre-allocate with_capacity
"Need to parallelize"
↓ m07-concurrency: Choose rayon or threads
↓ m07-concurrency: Consider async for I/O-bound
"Need cache efficiency"
↓ Data layout: Prefer Vec over HashMap when possible
↓ Access patterns: Sequential over random access---
Quick Reference
| Tool | Purpose | |------|---------| | `cargo bench` | Micro-benchmarks | | `criterion` | Statistical benchmarks | | `perf` / `flamegraph` | CPU profiling | | `heaptrack` | Allocation tracking | | `valgrind` / `cachegrind` | Cache analysis |
Optimization Priority
1. Algorithm choice (10x - 1000x)
2. Data structure (2x - 10x)
3. Allocation reduction (2x - 5x)
4. Cache optimization (1.5x - 3x)
5. SIMD/Parallelism (2x - 8x)
Common Techniques
| Technique | When | How | |-----------|------|-----| | Pre-allocation | Known size | `Vec::with_capacity(n)` | | Avoid cloning | Hot paths | Use references or `Cow<T>` | | Batch operations | Many small ops | Collect then process | | SmallVec | Usually small | `smallvec::SmallVec<[T; N]>` | | Inline buffers | Fixed-size data | Arrays over Vec |
---
Common Mistakes
| Mistake | Why Wrong | Better | |---------|-----------|--------| | Optimize without profiling | Wrong target | Profile first | | Benchmark in debug mode | Meaningless | Always `--release` | | Use LinkedList | Cache unfriendly | `Vec` or `VecDeque` | | Hidden `.clone()` | Unnecessary allocs | Use references | | Premature optimization | Wasted effort | Make it work first |
---
Anti-Patterns
| Anti-Pattern | Why Bad | Better | |--------------|---------|--------| | Clone to avoid lifetimes | Performance cost | Proper ownership | | Box everything | Indirection cost | Stack when possible | | HashMap for small sets | Overhead | Vec with linear search | | String concat in loop | O(n^2) | `String::with_capacity` or `format!` |
---
Related Skills
| When | See | |------|-----| | Reducing clones | m01-ownership | | Concurrency options | m07-concurrency | | Smart pointer choice | m02-resource | | Domain requirements | domain-* |
Read more
name: m10-performance description: "CRITICAL: Use for performance optimization. Triggers: performance, optimization, benchmark, profiling, flamegraph, criterion, slow, fast, allocation, cache, SIMD, make it faster, 性能优化, 基准测试" user-invocable: false
Performance Optimization
> **Layer 2: Design Choices**
Core Question
**What's the bottleneck, and is optimization worth it?**
Before optimizing:
- Have you measured? (Don't guess)
- What's the acceptable performance?
- Will optimization add complexity?
---
Performance Decision → Implementation
| Goal | Design Choice | Implementation | |------|---------------|----------------| | Reduce allocations | Pre-allocate, reuse | `with_capacity`, object pools | | Improve cache | Contiguous data | `Vec`, `SmallVec` | | Parallelize | Data parallelism | `rayon`, threads | | Avoid copies | Zero-copy | References, `Cow<T>` | | Reduce indirection | Inline data | `smallvec`, arrays |
---
Thinking Prompt
Before optimizing:
1. **Have you measured?**
- Profile first → flamegraph, perf
- Benchmark → criterion, cargo bench
- Identify actual hotspots
2. **What's the priority?**
- Algorithm (10x-1000x improvement)
- Data structure (2x-10x)
- Allocation (2x-5x)
- Cache (1.5x-3x)
3. **What's the trade-off?**
- Complexity vs speed
- Memory vs CPU
- Latency vs throughput
---
Trace Up ↑
To domain constraints (Layer 3):
"How fast does this need to be?"
↑ Ask: What's the performance SLA?
↑ Check: domain-* (latency requirements)
↑ Check: Business requirements (acceptable response time)| Question | Trace To | Ask | |----------|----------|-----| | Latency requirements | domain-* | What's acceptable response time? | | Throughput needs | domain-* | How many requests per second? | | Memory constraints | domain-* | What's the memory budget? |
---
Trace Down ↓
To implementation (Layer 1):
"Need to reduce allocations"
↓ m01-ownership: Use references, avoid clone
↓ m02-resource: Pre-allocate with_capacity
"Need to parallelize"
↓ m07-concurrency: Choose rayon or threads
↓ m07-concurrency: Consider async for I/O-bound
"Need cache efficiency"
↓ Data layout: Prefer Vec over HashMap when possible
↓ Access patterns: Sequential over random access---
Quick Reference
| Tool | Purpose | |------|---------| | `cargo bench` | Micro-benchmarks | | `criterion` | Statistical benchmarks | | `perf` / `flamegraph` | CPU profiling | | `heaptrack` | Allocation tracking | | `valgrind` / `cachegrind` | Cache analysis |
Optimization Priority
1. Algorithm choice (10x - 1000x) 2. Data structure (2x - 10x) 3. Allocation reduction (2x - 5x) 4. Cache optimization (1.5x - 3x) 5. SIMD/Parallelism (2x - 8x)
Common Techniques
| Technique | When | How | |-----------|------|-----| | Pre-allocation | Known size | `Vec::with_capacity(n)` | | Avoid cloning | Hot paths | Use references or `Cow<T>` | | Batch operations | Many small ops | Collect then process | | SmallVec | Usually small | `smallvec::SmallVec<[T; N]>` | | Inline buffers | Fixed-size data | Arrays over Vec |
---
Common Mistakes
| Mistake | Why Wrong | Better | |---------|-----------|--------| | Optimize without profiling | Wrong target | Profile first | | Benchmark in debug mode | Meaningless | Always `--release` | | Use LinkedList | Cache unfriendly | `Vec` or `VecDeque` | | Hidden `.clone()` | Unnecessary allocs | Use references | | Premature optimization | Wasted effort | Make it work first |
---
Anti-Patterns
| Anti-Pattern | Why Bad | Better | |--------------|---------|--------| | Clone to avoid lifetimes | Performance cost | Proper ownership | | Box everything | Indirection cost | Stack when possible | | HashMap for small sets | Overhead | Vec with linear search | | String concat in loop | O(n^2) | `String::with_capacity` or `format!` |
---
Related Skills
| When | See | |------|-----| | Reducing clones | m01-ownership | | Concurrency options | m07-concurrency | | Smart pointer choice | m02-resource | | Domain requirements | domain-* |
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