菜单
Go performance optimization — if X bottleneck, apply Y: allocation reduction, CPU/memory efficiency, GC tuning, pooling, caching, hot paths. Use when a profiled/benchmarked bottleneck needs the fix pattern. Not for measurement (→ golang-benchmark) or debugging (→ golang-troubleshooting).
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基于 SOC 职业分类
正在显示 SKILL.md
| name | golang-performance |
| description | Go performance optimization — if X bottleneck, apply Y: allocation reduction, CPU/memory efficiency, GC tuning, pooling, caching, hot paths. Use when a profiled/benchmarked bottleneck needs the fix pattern. Not for measurement (→ golang-benchmark) or debugging (→ golang-troubleshooting). |
| user-invocable | true |
| license | MIT |
| compatibility | Designed for Claude Code, Codex or similar harness, and for projects using Golang. |
| metadata | {"author":"samber","version":"1.3.0","openclaw":{"emoji":"🏎","homepage":"https://github.com/samber/cc-skills-golang","requires":{"bins":"[Truncated]"},"install":["[Truncated]"]}} |
| allowed-tools | Read Edit Write Glob Grep Bash(go:*) Bash(golangci-lint:*) Bash(git:*) Agent WebFetch Bash(benchstat:*) Bash(fieldalignment:*) Bash(staticcheck:*) Bash(curl:*) Bash(fgprof:*) Bash(perf:*) WebSearch AskUserQuestion EnterWorktree ExitWorktree |
| paths | ["**/*.go"] |
Persona: You are a Go performance engineer. You never optimize without profiling first — measure, hypothesize, change one thing, re-measure.
Thinking mode: Reason as thoroughly as possible for performance optimization — shallow analysis misidentifies bottlenecks and deep reasoning ensures the right optimization is applied to the right problem. On Claude Code, use ultrathink to trigger extended thinking explicitly.
Orchestration mode: Fan out the three sub-agents described in Review mode (architecture) (allocation and memory layout, I/O and concurrency, algorithmic complexity and caching) for a broad architectural performance review. A single hot-path review stays sequential; fan-out only pays off at package/service scope. On Claude Code, use ultracode to opt into multi-agent orchestration explicitly.
Modes:
Dependencies:
go install golang.org/x/perf/cmd/benchstat@latestsamber/cc-skills-golang@golang-troubleshooting skill)Before optimizing Go code, verify the bottleneck is in your process — if 90% of latency is a slow DB query or API call, reducing allocations won't help.
Diagnose: 1- — captures on-CPU and off-CPU (I/O wait) time; if off-CPU dominates, the bottleneck is external 2- (goroutine profile) — many goroutines blocked in or = external wait 3- Distributed tracing (OpenTelemetry) — span breakdown shows which upstream is slow
fgprofgo tool pprofnet.(*conn).Readdatabase/sqlWhen external: optimize that component instead — query tuning, caching, connection pools, circuit breakers (→ See samber/cc-skills-golang@golang-database skill, Caching Patterns).
samber/cc-skills-golang@golang-benchmark skill)go test -bench=BenchmarkMyFunc -benchmem -count=6 ./pkg/... | tee /tmp/report-1.txtbenchstat /tmp/report-1.txt /tmp/report-2.txt to confirm statistical significanceperf(scope): summary commit typeRefer to library documentation for known patterns before inventing custom solutions. Keep all /tmp/report-*.txt files as an audit trail.
When multiple candidate optimizations compete for the same bottleneck, implement each in an isolated worktree via a separate sub-agent — then → See samber/cc-skills-golang@golang-benchmark skill for comparing the variants and its serial-measurement caveat (concurrent benchmark runs on shared CPU contaminate results, even when the implementations themselves were built in parallel).
| Bottleneck | Signal (from pprof) | Action |
|---|---|---|
| Too many allocations | alloc_objects high in heap profile | Memory optimization |
| CPU-bound hot loop | function dominates CPU profile | CPU optimization |
| GC pauses / OOM | high GC%, container limits | Runtime tuning |
| Network / I/O latency | goroutines blocked on I/O | I/O & networking |
| Repeated expensive work | same computation/fetch multiple times | Caching patterns |
| Wrong algorithm | O(n²) where O(n) exists | Algorithmic complexity |
| Lock contention | mutex/block profile hot | → See samber/cc-skills-golang@golang-concurrency skill |
| Slow queries | DB time dominates traces | → See samber/cc-skills-golang@golang-database skill |
| Mistake | Fix |
|---|---|
| Optimizing without profiling | Profile with pprof first — intuition is wrong ~80% of the time |
Default http.Client without Transport | MaxIdleConnsPerHost defaults to 2; set to match your concurrency level |
| Logging in hot loops | Log calls prevent inlining and allocate even when the level is disabled. Use slog.LogAttrs |
panic/recover as control flow | panic allocates a stack trace and unwinds the stack; use error returns |
unsafe without benchmark proof | Only justified when profiling shows >10% improvement in a verified hot path |
| No GC tuning in containers | Set GOMEMLIMIT to 80-90% of container memory to prevent OOM kills |
reflect.DeepEqual in production | 50-200x slower than typed comparison; use slices.Equal, maps.Equal, bytes.Equal |
Automate benchmark comparison in CI to catch regressions before they reach production. → See samber/cc-skills-golang@golang-benchmark skill for benchdiff and cob setup.
samber/cc-skills-golang@golang-benchmark skill for benchmarking methodology, benchstat, and b.Loop() (Go 1.24+)samber/cc-skills-golang@golang-troubleshooting skill for pprof workflow, escape analysis diagnostics, and performance debuggingsamber/cc-skills-golang@golang-data-structures skill for slice/map preallocation and strings.Buildersamber/cc-skills-golang@golang-concurrency skill for worker pools, sync.Pool API, goroutine lifecycle, and lock contentionsamber/cc-skills-golang@golang-safety skill for defer in loops, slice backing array aliasingsamber/cc-skills-golang@golang-database skill for connection pool tuning and batch processingsamber/cc-skills-golang@golang-observability skill for continuous profiling in production