Agent skill

Golang Benchmark

by aiskillstore in aiskillstore/marketplace

Golang benchmarking, profiling, and performance measurement.

MITAuto-check passedDevOps & Cloud

Install Golang Benchmark

skills CLI
$ npx skills add aiskillstore/marketplace --skill golang-benchmark -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aiskillstore/marketplace golang-benchmark --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aiskillstore/marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/samber/golang-benchmark .claude/skills/golang-benchmark && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
golang-benchmark
GitHub stars
433
Used in
1 other repo
Token cost
~3.4k tokens
SKILL.md length
1,239 words
Files
11 (incl. references)
Skills in repo
1,044
Repo updated
First seen
Licence
MIT

At a glance

Golang benchmarking, profiling, and performance measurement.

  • Comparing Go benchmarks
  • SKILL.md covers Writing Benchmarks, Running Benchmarks, Comparing Optimization… and Documenting Results in Commits, plus 3 more sections
  • Calls go
  • Profiling hot paths with pprof

What it does

Golang Benchmark is an agent skill from aiskillstore/marketplace. Golang benchmarking, profiling, and performance measurement. Use when writing, running, or comparing Go benchmarks, profiling hot paths with pprof, interpreting CPU/memory/trace profiles, analyzing results with benchstat, setting up CI benchmark regression detection, or investigating production performance with Prometheus runtime metrics. Also use when the developer needs deep analysis on a specific performance indicator - this skill provides the measurement methodology, while…

Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files, including reference files (for example `evals/evals.json`, `references/benchstat.md` and `references/ci-regression.md`). Compatibility notes: Designed for Claude Code, Codex or similar harness, and for projects using Golang.

It sits in DevOps & Cloud, covering Monitoring and alerting. It works with Go and Prometheus. The repository describes itself as: Security-audited skills for Claude, Codex & Claude Code. One-click install, quality verified. The licence is MIT.

When your agent uses it

  • Comparing Go benchmarks
  • Profiling hot paths with pprof
  • Interpreting CPU/memory/trace profiles
  • Analyzing results with benchstat

Example prompts

  • “/golang-benchmark”

Requirements

  • Compatibility (from SKILL.md): Designed for Claude Code, Codex or similar harness, and for projects using Golang.
  • Pre-approved tools (allowed-tools): Read, Edit, Write, Glob, Grep, Bash(go:*), Bash(golangci-lint:*), Bash(git:*), Agent, WebFetch, Bash(benchstat:*), Bash(benchdiff:*), Bash(cob:*), Bash(gobenchdata:*), Bash(curl:*), mcp__context7__resolve-library-id, mcp__context7__query-docs, WebSearch, AskUserQuestion, EnterWorktree, ExitWorktree

What it can do on your machine

Read from SKILL.md and the folder at commit 44923f3. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Edit
    • Write
    • Glob
    • Grep
    • Bash(go:*)
    • Bash(golangci-lint:*)
    • Bash(git:*)
    • Agent
    • WebFetch

    …and 11 more on the same allowed-tools line.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • go

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code, Codex or similar harness, and for projects using Golang.

    From compatibility in the SKILL.md frontmatter.

Context cost

Golang Benchmark loads about 3.4k tokens when it runs, and up to ~34k if it reads all its reference files. Until then it costs about 145 tokens; SKILL.md has 1,239 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~145
When it runs · the whole SKILL.md, loaded when a task matches
~3.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~34k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from aiskillstore/marketplace at commit 44923f3, republished under its MIT licence (© aiskillstore). 1,239 words, ~3,423 tokens.

Download SKILL.mdSave it as .claude/skills/golang-benchmark/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.
name
golang-benchmark
description
Golang benchmarking, profiling, and performance measurement. Use when writing, running, or comparing Go benchmarks, profiling hot paths with pprof, interpreting CPU/memory/trace profiles, analyzing results with benchstat, setting up CI benchmark regression detection, or investigating production performance with Prometheus runtime metrics. Also use when the developer needs deep analysis on a specific performance indicator - this skill provides the measurement methodology, while `samber/cc-skills-golang@golang-performance` provides the optimization patterns.
allowed-tools
Read, Edit, Write, Glob, Grep, Bash(go:*), Bash(golangci-lint:*), Bash(git:*), Agent, WebFetch, Bash(benchstat:*), Bash(benchdiff:*), Bash(cob:*), Bash(gobenchdata:*), Bash(curl:*), mcp__context7__resolve-library-id, mcp__context7__query-docs, WebSearch, AskUserQuestion, EnterWorktree, ExitWorktree
compatibility
Designed for Claude Code, Codex or similar harness, and for projects using Golang.
user-invocable
true
license
MIT
metadata.author
samber
metadata.version
1.3.2
paths
**/*.go

Persona: You are a Go performance measurement engineer. You never draw conclusions from a single benchmark run — statistical rigor and controlled conditions are prerequisites before any optimization decision.

Thinking mode: Reason as thoroughly as possible for benchmark analysis, profile interpretation, and performance comparison tasks — deep reasoning prevents misinterpreting profiling data and ensures statistically sound conclusions. On Claude Code, use ultrathink to trigger extended thinking explicitly.

Dependencies:

  • benchstat: go install golang.org/x/perf/cmd/benchstat@latest

Go Benchmarking & Performance Measurement

Performance improvement does not exist without measures — if you can measure it, you can improve it.

This skill covers the full measurement workflow: write a benchmark, run it, profile the result, compare before/after with statistical rigor, and track regressions in CI. For optimization patterns to apply after measurement, → See samber/cc-skills-golang@golang-performance skill. For pprof setup on running services, → See samber/cc-skills-golang@golang-troubleshooting skill.

Writing Benchmarks

File and Ordering Conventions

Benchmark functions live in a _bench_test.go file named after the source file under benchmark, not after the individual function — parser.go -> parser_bench_test.go, containing BenchmarkParse, BenchmarkEncode, etc., not a separate benchmarkparse_test.go per function.

  • Keeping benchmarks in their own file (instead of mixed into parser_test.go) keeps go test -bench=. ./pkg/parser output free of unrelated Test* noise.
  • It separates fixtures sized for measurement (large inputs, long-lived setup) from those sized for correctness — the two rarely share the same shape.
  • The file still follows Go's one-test-file-per-source-file convention (→ See samber/cc-skills-golang@golang-testing skill), just with the _bench suffix marking its narrower purpose.

Order Benchmark* functions inside parser_bench_test.go to mirror the order of the functions/methods they measure in parser.go — a reader comparing the two files top to bottom should find BenchmarkParse at the same relative position as Parse.

b.Loop() (Go 1.24+) — preferred

For Go 1.24+, prefer b.Loop() for new benchmarks. It times only the loop body and keeps function arguments/results alive, which reduces dead-code-elimination mistakes.

go
func BenchmarkParse(b *testing.B) {
    data := loadFixture("large.json") // setup — excluded from timing
    for b.Loop() {
        Parse(data)  // compiler cannot eliminate this call
    }
}

Legacy b.N loops still compile and are fine to keep when preserving existing benchmarks or supporting Go <1.24. They are easier to get wrong: setup may need b.ResetTimer(), and results may need a sink if the compiler can eliminate the work. Go 1.26 fixed an earlier b.Loop() inlining limitation — benchmarks on 1.24–1.25 already benefit from b.Loop() but may miss inlining optimizations that 1.26 delivers.

Go 1.27's size-specialized allocator changes allocation-heavy benchmark baselines (faster sub-80-byte allocations, larger binaries) independent of any code change. Treat a benchstat comparison that straddles the Go 1.26→1.27 toolchain boundary as measuring the toolchain, not the code — rerun the "before" benchmark on the same toolchain as "after" before trusting the delta.

Memory tracking
go
func BenchmarkAlloc(b *testing.B) {
    b.ReportAllocs() // or run with -benchmem flag
    var sink []byte
    for b.Loop() {
        sink = make([]byte, 1024)
    }
    _ = sink
}

b.ReportMetric() adds custom metrics (e.g., throughput):

go
b.ReportMetric(float64(totalBytes)/b.Elapsed().Seconds(), "bytes/s") // b.Elapsed() is only valid inside b.Loop()
Sub-benchmarks and table-driven
go
func BenchmarkEncode(b *testing.B) {
    for _, size := range []int{64, 256, 4096} {
        b.Run(fmt.Sprintf("size=%d", size), func(b *testing.B) {
            data := make([]byte, size)
            for b.Loop() {
                Encode(data)
            }
        })
    }
}

Running Benchmarks

bash
go test -bench=BenchmarkEncode -benchmem -count=10 ./pkg/... | tee bench.txt
FlagPurpose
-bench=.Run all benchmarks (regexp filter)
-benchmemReport allocations (B/op, allocs/op)
-count=10Run 10 times for statistical significance
-benchtime=3sMinimum time per benchmark (default 1s)
-cpu=1,2,4Run with different GOMAXPROCS values
-cpuprofile=cpu.profWrite CPU profile
-memprofile=mem.profWrite memory profile
-trace=trace.outWrite execution trace

Output format: BenchmarkEncode/size=64-8 5000000 230.5 ns/op 128 B/op 2 allocs/op — the -8 suffix is GOMAXPROCS, ns/op is time per operation, B/op is bytes allocated per op, allocs/op is heap allocation count per op.

Comparing Optimization Variants in Parallel

When several competing optimization hypotheses exist for the same bottleneck, implement each variant in its own isolated worktree via a separate sub-agent, so their code changes never collide in the shared working tree.

Run the benchmarks serially, not concurrently. Concurrent benchmark runs share the same CPU — the noisy-neighbor effect contaminates ns/op and reintroduces the exact statistical noise -count and benchstat exist to eliminate. Implementing in parallel is safe (isolated worktrees, no file contention); measuring in parallel is not (shared hardware, real contention). Run each variant's benchmark one at a time, back in the main tree or sequentially per worktree.

Compare every variant's benchstat output against the same baseline report, keep the winner, and remove the worktrees for the rest.

Documenting Results in Commits

Paste benchstat output in the commit body when the change has a measurable performance impact. This documents why an optimization was made, prevents future readers from reverting it, and lets reviewers verify the claim without re-running benchmarks.

Commit format:

perf(parser): reduce Parse allocations 50% with sync.Pool

Replace per-call []byte allocation with a pooled buffer.

goos: linux / goarch: amd64 / cpu: AMD Ryzen 9 5950X
          │    old     │              new               │
          │  sec/op    │  sec/op     vs base            │
Parse-32    4.592µ ± 2%  3.041µ ± 1%  -33.78% (p=0.000 n=10)

          │   old    │             new              │
          │   B/op   │   B/op     vs base           │
Parse-32   1.024Ki ± 0%  0.512Ki ± 0%  -50.00% (p=0.000 n=10)

          │ old  │            new             │
          │ allocs/op │ allocs/op  vs base    │
Parse-32   12.00 ± 0%   6.000 ± 0%  -50.00% (p=0.000 n=10)

Rules:

  • Only include benchmarks directly affected by the change — strip unrelated rows
  • Never paste results with ~ (no statistical significance) — the improvement cannot be claimed
  • Include the hardware context line (goos/goarch/cpu) so results are reproducible
  • Use perf(scope): commit type for performance-only changes

Profiling from Benchmarks

Generate profiles directly from benchmark runs — no HTTP server needed:

bash
# CPU profile
go test -bench=BenchmarkParse -cpuprofile=cpu.prof ./pkg/parser
go tool pprof cpu.prof

# Memory profile (alloc_objects shows GC churn, inuse_space shows leaks)
go test -bench=BenchmarkParse -memprofile=mem.prof ./pkg/parser
go tool pprof -alloc_objects mem.prof

# Execution trace
go test -bench=BenchmarkParse -trace=trace.out ./pkg/parser
go tool trace trace.out

For full pprof CLI reference (all commands, non-interactive mode, profile interpretation), see pprof Reference. For execution trace interpretation, see Trace Reference. For statistical comparison, see benchstat Reference.

Show full SKILL.md (490 more words)Show less

Reference Files

  • pprof Reference — Interactive and non-interactive analysis of CPU, memory, and goroutine profiles. Full CLI commands, profile types (CPU vs allocobjects vs inuse_space), web UI navigation, and interpretation patterns. Use this to dive deep into _where time and memory are being spent in your code.

  • benchstat Reference — Statistical comparison of benchmark runs with rigorous confidence intervals and p-value tests. Covers output reading, filtering old benchmarks, interleaving results for visual clarity, and regression detection. Use this when you need to prove a change made a meaningful performance difference, not just a lucky run.

  • Trace Reference — Execution tracer for understanding when and why code runs. Visualizes goroutine scheduling, garbage collection phases, network blocking, and custom span annotations. Use this when pprof (which shows where CPU goes) isn't enough — you need to see the timeline of what happened.

  • Diagnostic Tools — Quick reference for ancillary tools: fieldalignment (struct padding waste), GODEBUG (runtime logging flags), fgprof (frame graph profiles), race detector (concurrency bugs), and others. Use this when you have a specific symptom and need a focused diagnostic — don't reach for pprof if a simpler tool already answers your question.

  • Compiler Analysis — Low-level compiler optimization insights: escape analysis (when values move to the heap), inlining decisions (which function calls are eliminated), SSA dump (intermediate representation), and assembly output. Use this when benchmarks show allocations you didn't expect, or when you want to verify the compiler did what you intended.

  • CI Regression Detection — Automated performance regression gating in CI pipelines. Covers three tools (benchdiff for quick PR comparisons, cob for strict threshold-based gating, gobenchdata for long-term trend dashboards), noisy neighbor mitigation strategies (why cloud CI benchmarks vary 5-10% even on quiet machines), and self-hosted runner tuning to make benchmarks reproducible. Use this when you want to ensure pull requests don't silently slow down your codebase — detecting regressions early prevents shipping performance debt.

  • Investigation Session — Production performance troubleshooting workflow combining Prometheus runtime metrics (heap size, GC frequency, goroutine counts), PromQL queries to correlate metrics with code changes, runtime configuration flags (GODEBUG env vars to enable GC logging), and cost warnings (when you're hitting performance tax). Use this when production benchmarks look good but real traffic behaves differently.

  • Prometheus Go Metrics Reference — Complete listing of Go runtime metrics actually exposed as Prometheus metrics by prometheus/client_golang. Covers 30 default metrics, 40+ optional metrics (Go 1.17+), process metrics, and common PromQL queries. Distinguishes between runtime/metrics (Go internal data) and Prometheus metrics (what you scrape from /metrics). Use this when setting up monitoring dashboards or writing PromQL queries for production alerts.

Cross-References

  • → See samber/cc-skills-golang@golang-performance skill for optimization patterns to apply after measuring ("if X bottleneck, apply Y")
  • → See samber/cc-skills-golang@golang-troubleshooting skill for pprof setup on running services (enable, secure, capture), Delve debugger, GODEBUG flags, root cause methodology
  • → See samber/cc-skills-golang@golang-observability skill for everyday always-on monitoring, continuous profiling (Pyroscope), distributed tracing (OpenTelemetry)
  • → See samber/cc-skills-golang@golang-testing skill for general testing practices
  • → See samber/cc-skills@promql-cli skill for querying Prometheus runtime metrics in production to validate benchmark findings

© aiskillstore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 10 other files (references) in skills/samber/golang-benchmark of aiskillstore/marketplace.

  • SKILL.md
  • evals/evals.json
  • references/benchstat.md
  • references/ci-regression.md
  • references/compiler-analysis.md
  • references/investigation-session.md
  • references/pprof.md
  • references/prometheus-go-metrics.md
  • references/tools.md
  • references/trace.md
  • skill-report.json

Open the folder on GitHubat commit 44923f3

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in aiskillstore/marketplace, which our catalogue first saw on October 7, 2026.

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Works with

Categories

Questions about Golang Benchmark

What does Golang Benchmark do?

Golang benchmarking, profiling, and performance measurement. Golang Benchmark is an agent skill from aiskillstore/marketplace. Golang benchmarking, profiling, and performance measurement.

When should I use Golang Benchmark?

Golang Benchmark fits situations like: comparing Go benchmarks; profiling hot paths with pprof; interpreting CPU/memory/trace profiles; analyzing results with benchstat.

How do I install Golang Benchmark in Claude Code?

Run `npx skills add aiskillstore/marketplace --skill golang-benchmark -a claude-code`. Or copy the skill folder (skills/samber/golang-benchmark in aiskillstore/marketplace) into .claude/skills/golang-benchmark in your project. Claude Code loads it when a task matches its description.

How do I install Golang Benchmark in Codex?

Run `npx skills add aiskillstore/marketplace --skill golang-benchmark -a codex`. Or copy the skill folder (skills/samber/golang-benchmark in aiskillstore/marketplace) into .agents/skills/golang-benchmark in your project. Codex loads it when a task matches its description.

Can I use Golang Benchmark in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aiskillstore/marketplace --skill golang-benchmark -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/golang-benchmark, .gemini/skills/golang-benchmark, .github/skills/golang-benchmark and .opencode/skills/golang-benchmark in your project.

What does Golang Benchmark need to run?

Going by SKILL.md and its folder, Golang Benchmark needs the command-line tools its instructions call (go). Its frontmatter pre-approves these tools: Read, Edit, Write, Glob, Grep, Bash(go:*), Bash(golangci-lint:*), Bash(git:*), Agent, WebFetch, Bash(benchstat:*), Bash(benchdiff:*), Bash(cob:*), Bash(gobenchdata:*), Bash(curl:*), mcp__context7__resolve-library-id, mcp__context7__query-docs, WebSearch, AskUserQuestion, EnterWorktree, ExitWorktree. Compatibility (from SKILL.md): Designed for Claude Code, Codex or similar harness, and for projects using Golang..

Does Golang Benchmark access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Golang Benchmark safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Golang Benchmark use?

Golang Benchmark is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Golang Benchmark use?

About 3.4k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 31k tokens, read only when the agent opens those files.

What are the alternatives to Golang Benchmark?

Skills that share tags, products or a category with Golang Benchmark: Devnet Triage (geanlabs/gean, 177 stars), Golang Samber Hot (samber/cc-skills-golang, 3.4k stars), Golang Observability (context-labs/whip, 1.1k stars) and Syncmeta (pawurb/hotpath-rs, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Golang Benchmark?

aiskillstore (a GitHub organization) maintains it in aiskillstore/marketplace, which has 433 GitHub stars. The repository holds 1,044 skills in this directory. The repository was last updated on October 10, 2026.

Source: aiskillstore/marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.