golang-performance
The golang-performance skill provides a structured methodology and pattern library for optimizing Go applications. It emphasizes data-driven performance engineering through profiling, iterative benchmarking, and specific optimization patterns for memory, CPU, I/O, and runtime tuning.
Is golang-performance safe to install?
Review the source first: our audit of golang-performance's source files found 3 shell commands, 0 external URLs, file reads and writes (high risk). Every command and URL listed appears verbatim in the skill's source. The skill executes shell commands including benchmark suites and performance analysis tools. It reads and writes files to the local filesystem, specifically creating and managing report files in /tmp/.
How we audit skills: our security review methodology.
Who is this skill for?
Go developers and performance engineers using AI coding agents to identify and resolve performance bottlenecks in Go projects.
What can you do with it?
- Performing architectural performance reviews to identify structural anti-patterns.
- Analyzing hot paths in functions or loops to improve execution efficiency.
- Applying iterative optimization cycles using benchmarks and statistical comparison.
- Diagnosing performance bottlenecks using pprof, fgprof, and distributed tracing.
- Tuning Go runtime parameters like GOMEMLIMIT and GOGC for containerized environments.
How good is this skill?
Quality score: 5/10. The skill provides a clear, actionable methodology for performance engineering. It includes specific commands, a decision tree for identifying bottlenecks, and explicit cross-references to related skills.
What does the skill file contain?
**Persona:** You are a Go performance engineer. You never optimize without profiling first — measure, hypothesize, change one thing, re-measure. **Thinking mode:** Use `ultrathink` for performance optimization. Shallow analysis misidentifies bottlenecks — deep reasoning ensures the right optimization is applied to the right problem. **Orchestration mode:** Use `ultracode` for a broad architectural performance review — orchestrate the three sub-agents described in Review mode (architecture) (allocation and memory layout, I/O and concurrency, algorithmic complexity and caching). A single hot-p...
Frequently asked questions
What is the recommended workflow for optimizing Go code?
The skill mandates a cycle of defining metrics, writing atomic benchmarks, measuring a baseline, diagnosing with profiling tools, applying one optimization at a time, comparing results with benchstat, and committing the findings.
How does the skill handle external bottlenecks?
It requires verifying if the bottleneck is external using tools like fgprof or pprof. If the bottleneck is external, such as slow database queries or API calls, it directs the user to optimize those components rather than the Go code.
Which tools are required for this skill?
The skill requires the Go toolchain and the benchstat utility from golang.org/x/perf/cmd/benchstat.
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