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 overviewgit 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/overview)<a href="https://agentmods.dev/skills/onsi/ginkgo/overview"><img src="https://agentmods.dev/badge/skills/onsi/ginkgo/overview/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/overview"><img src="https://agentmods.dev/badge/skills/onsi/ginkgo/overview.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 | $0.00084 | $0.01280 |
| Opus 5.5 | $0.00034 | $0.00512 |
| Sonnet 5.5 | $0.00017 | $0.00256 |
| Haiku 4.5 | $0.00008 | $0.00128 |
Grade A, and why
overview 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ginkgo: the mental model
Ginkgo is an expressive BDD-style testing framework for Go, paired with the Gomega matcher library. You build suites out of nested container nodes (Describe/Context/When) and subject nodes (It), with setup nodes (BeforeEach/AfterEach/…) supplying state. You drive it with the ginkgo CLI. Strongly prefer ginkgo over go test.
Read the canonical narrative docs at https://onsi.github.io/ginkgo/ — they are the source of truth. This skill is the orientation; the other skills go deep.
The one idea: tree construction, then running
Ginkgo runs your suite in two distinct phases. Internalizing this explains nearly every Ginkgo gotcha:
- Tree-construction phase. Ginkgo invokes every container body exactly once to discover the structure of your suite. It collects — but does not run — the closures you pass to setup and subject nodes. The result is a tree it flattens into a list of specs.
- Run phase. Ginkgo walks the flattened spec list (randomized, possibly in parallel) and, for each spec, runs its setup closures, then its one subject closure, then its cleanup closures.
Container bodies run at construction time. Setup/subject closures run later, at run time. The consequences you must internalize:
- No assertions in container bodies. They'd run once during construction, with no spec active — not as part of any test. Put assertions in
ItorBeforeEach. - No initialization in container bodies. A variable set in a
Describebody is set once, shared across every spec, and mutated by whichever spec runs first. Declare in the container, initialize inBeforeEachso every spec gets a pristine copy. →ginkgo:writing-specs. - Loops that build specs run at construction time — that's how you generate specs dynamically, but it also means closure-captured loop variables and any data the loop reads must be available then, not in
BeforeSuite. →ginkgo:tables-and-dynamic-specs.
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 First seen · 57 lines · 84 tokens per session scan A 9b0de0a29ee3
overview is a skill published in the GitHub repository onsi/ginkgo (9,066 stars, last pushed 9d ago), licensed MIT. It adds 84 tokens to every session and 1,280 once invoked, about $0.0003 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.
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