Ginkgo is a Go testing framework for writing organized, expressive specifications, including unit, integration, and performance tests. Go developers use it with the Gomega matcher library to describe behavior and run test suites.
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/ginkgo --skill cigit clone --depth 1 https://github.com/onsi/ginkgoWrote 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/ginkgo/ci)<a href="https://agentmods.dev/skills/onsi/ginkgo/ci"><img src="https://agentmods.dev/badge/skills/onsi/ginkgo/ci/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/ginkgo/ci"><img src="https://agentmods.dev/badge/skills/onsi/ginkgo/ci.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 | $0.00151 | $0.01689 |
| Opus 5.5 | $0.00060 | $0.00676 |
| Sonnet 5.5 | $0.00030 | $0.00338 |
| Haiku 4.5 | $0.00015 | $0.00169 |
Grade A, and why
ci 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 1mo 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ginkgo in CI
A CI invocation should maximize signal — surface flakes and spec pollution, catch mistakes that pass locally, and emit machine-readable artifacts — while collecting every failure in one run. This builds on the CLI (ginkgo:running) and report formats (ginkgo:reporting). Full rationale: https://onsi.github.io/ginkgo/#recommended-continuous-integration-configuration.
The recommended flag set
Invoke via go run so the CLI version always tracks the github.com/onsi/ginkgo/v2 in your go.mod — no separately-installed binary to drift (→ ginkgo:setup).
go run github.com/onsi/ginkgo/v2/ginkgo \
-r -p --randomize-all --randomize-suites \
--fail-on-pending --fail-on-empty --keep-going \
--cover --coverprofile=cover.profile --race --trace \
--json-report=report.json --output-dir=.ginkgo-report \
--timeout=TIMEOUT --poll-progress-after=Xs --poll-progress-interval=Ys
| Flag | Why |
|---|---|
-r |
recursively find and run every suite |
-p |
run each suite in parallel (→ ginkgo:parallelism; set --procs=N/--compilers=N if CPU detection is wrong) |
--randomize-all / --randomize-suites |
shuffle all specs and the suite order to surface spec pollution (→ ginkgo:running) |
--fail-on-pending |
fail if any Pending specs were committed |
--fail-on-empty |
fail if no specs ran (usually a malformed filter) |
--keep-going |
don't stop at the first failed suite — collect all failures |
--cover --coverprofile=cover.profile |
compute coverage into one merged profile (→ ginkgo:reporting) |
--race |
run with the race detector (costs a fixed ~1s per suite — see below) |
--trace |
full stack traces on failure (worth it without a local feedback loop) |
--json-report=report.json |
structured results for diagnosis and downstream tools (→ ginkgo:debugging-failures) |
--timeout=TIMEOUT |
cap the whole run (default 1h — often not enough) |
--poll-progress-after/--poll-progress-interval |
emit progress reports for stuck specs (→ ginkgo:timeouts-and-async) |
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.
- 1mo ago Changed · +14 lines · +19 tokens per session 1400648291cd
- 1mo ago First seen · 71 lines · 132 tokens per session scan A 01db01e326ad
ci is a skill published in the GitHub repository onsi/ginkgo (9,066 stars, last pushed 8d ago), licensed MIT. It adds 151 tokens to every session and 1,689 once invoked, about $0.0006 per session on Opus 5.5. 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.
Other skills, from other repositories
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samurai
Samurai scoped testing framework for Go (github.com/zerosixty/samurai). MUST use when writing, modifying, reviewing, or debugging Go tests that import samurai, or reference samurai.Run, samurai.RunWith, samurai.Scope, samurai.TestScope, samurai.W, or samurai.BaseContext.
ci-cd
CI/CD pipelines for GitHub Actions and Docker-based deployments — lint, test, build, push, deploy stages; environment secrets; branch-gated workflows; health-check rollbacks; and PM2/systemd service restarts.
golang-testing
Go testing best practices including table-driven tests, test helpers, benchmarking, race detection, coverage analysis, and integration testing patterns. Use when writing or improving Go tests.
quality-scan
Run a scoped, read-only quality scan and report exact-candidate evidence, failures and frozen debt. Use for an ad-hoc gate sweep or release preparation; a static scan is not full release acceptance.
e2e-testing
Use when reviewing CI coverage, automated checks, or test strategy related to Implement end-to-end testing. Focus on whether the rule is continuously verified, not just documented.