Gomega is a Go library for writing test assertions with matchers, including support for asynchronous checks and several specialized testing sub-libraries. It is used by Go developers, especially alongside the Ginkgo behavior-driven testing framework, to express and evaluate test expectations. The catalogue entries are Claude Code skills and a plugin that help agents use Gomega's matchers and testing idioms.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add onsi/gomega --skill gmeasuregit clone --depth 1 https://github.com/onsi/gomegaWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/onsi/gomega/gmeasure)<a href="https://agentmods.dev/skills/onsi/gomega/gmeasure"><img src="https://agentmods.dev/badge/skills/onsi/gomega/gmeasure/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/onsi/gomega/gmeasure"><img src="https://agentmods.dev/badge/skills/onsi/gomega/gmeasure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00129 | $0.02020 |
| Opus 5 | $0.00064 | $0.01010 |
| Sonnet 5 | $0.00026 | $0.00404 |
| Haiku 4.5 | $0.00013 | $0.00202 |
Grade A, and why
gmeasure scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
gmeasure: benchmarking and measuring code
gmeasure records benchmarks as Experiments that hold one or more named Measurements. Use it standalone (fmt.Println(experiment)) or wire it into Ginkgo for rich report output. Docs: https://onsi.github.io/gomega/#gmeasure-benchmarking-code. For the broader library see gomega:overview.
import "github.com/onsi/gomega/gmeasure"
Mental model
- An Experiment (
gmeasure.NewExperiment(name)) groups related measurements for one system/context. - A Measurement is a named bag of data points plus a
Type:MeasurementTypeValue(float64) orMeasurementTypeDuration(time.Duration). It is created on its first recorded data point; later records of the same name append. - Stats are statistical aggregates (min/max/mean/median/stddev) computed over a measurement's data points.
gmeasure does not fail tests by itself. It is a benchmarking/reporting tool. To gate on results you must pull Stats and write your own Expect(...) (or use RankStats(...).Winner()).
experiment := gmeasure.NewExperiment("My Experiment")
experiment.RecordDuration("runtime", 3*time.Second) // creates the "runtime" measurement
experiment.RecordDuration("runtime", 5*time.Second) // appends a data point
Recording values and durations
// Direct values / durations:
experiment.RecordValue("length", 3.141)
experiment.RecordDuration("runtime", 200*time.Millisecond)
// Callback-driven — gmeasure times MeasureDuration for you:
v := experiment.MeasureValue("length", func() float64 { return computeLength() })
d := experiment.MeasureDuration("save", func() { client.Save(model) })
Experiments are thread-safe — RecordX/MeasureX may be called from any goroutine.
Sampling: ensembles of data points
Run a callback repeatedly to build up many data points. Configure with SamplingConfig:
type SamplingConfig struct {
N int // cap on number of samples
Duration time.Duration // cap on total sampling time
NumParallel int // run samples across this many goroutines (>1)
MinSamplingInterval time.Duration // minimum gap between samples (incompatible with NumParallel)
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 189 lines · 129 tokens per session scan A 5e07e47a5a4d
gmeasure is a skill published in the GitHub repository onsi/gomega (2,355 stars, last pushed 12d ago), licensed MIT. It adds 129 tokens to every session and 2,020 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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