Skill detail
golang-performance
Go performance optimization patterns and methodology, including a performance code review mode for allocation, CPU, memory, and hot-path issues.
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SKILL.md
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---
name: golang-performance
description: "Golang performance optimization patterns and methodology - if X bottleneck, then apply Y. Covers allocation reduction, CPU efficiency, memory layout, GC tuning, pooling, caching, and hot-path optimization. Use when profiling or benchmarks have identified a bottleneck and you need the right optimization pattern to fix it. Also use when performing performance code review to suggest improvements or benchmarks that could help identify quick performance gains. Not for measurement methodology (→ See `samber/cc-skills-golang@golang-benchmark` skill) or debugging workflow (→ See `samber/cc-skills-golang@golang-troubleshooting` skill)."
user-invocable: true
license: MIT
compatibility: Designed for Claude Code, Codex or similar harness, and for projects using Golang.
metadata:
author: samber
version: "1.3.2"
openclaw:
emoji: "🏎"
homepage: https://github.com/samber/cc-skills-golang
requires:
bins:
- go
- benchstat
install:
- kind: go
package: golang.org/x/perf/cmd/benchstat@latest
bins: [benchstat]
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:**
- **Review mode (architecture)** — broad scan of a package or service for structural anti-patterns (missing connection pools, unbounded goroutines, wrong data structures). Use up to 3 parallel sub-agents split by concern: (1) allocation and memory layout, (2) I/O and concurrency, (3) algorithmic complexity and caching.
- **Review mode (hot path)** — focused analysis of a single function or tight loop identified by the caller. Work sequentially; one sub-agent is sufficient.
- **Optimize mode** — a bottleneck has been identified by profiling. Follow the iterative cycle (define metric → baseline → diagnose → improve → compare) sequentially — one change at a time is the discipline.
**Dependencies:**
- benchstat: `go install golang.org/x/perf/cmd/benchstat@latest`
# Go Performance Optimization
## Core Philosophy
1. **Profile before optimizing** — intuition about bottlenecks is wrong ~80% of the time. Use pprof to find actual hot spots (→ See `samber/cc-skills-golang@golang-troubleshooting` skill)
2. **Allocation reduction yields the biggest ROI** — Go's GC is fast but not free. Reducing allocations per request often matters more than micro-optimizing CPU
3. **Document optimizations** — add code comments explaining why a pattern is faster, with benchmark numbers when available. Future readers need context to avoid reverting an "unnecessary" optimization
## Rule Out External Bottlenecks First
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- `fgprof` — captures on-CPU and off-CPU (I/O wait) time; if off-CPU dominates, the bottleneck is external 2- `go tool pprof` (goroutine profile) — many goroutines blocked in `nRead the full source on GitHub (opens external page)