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 debugging-failuresgit 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/debugging-failures)<a href="https://agentmods.dev/skills/onsi/ginkgo/debugging-failures"><img src="https://agentmods.dev/badge/skills/onsi/ginkgo/debugging-failures/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/debugging-failures"><img src="https://agentmods.dev/badge/skills/onsi/ginkgo/debugging-failures.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 | $0.00122 | $0.01824 |
| Opus 5.5 | $0.00049 | $0.00730 |
| Sonnet 5.5 | $0.00024 | $0.00365 |
| Haiku 4.5 | $0.00012 | $0.00182 |
Grade A, and why
debugging-failures 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debugging Ginkgo failures (especially as an agent)
Ginkgo's terminal output is good for a human; for programmatic diagnosis, prefer a hybrid: terminal for the verdict, JSON + jq for the details. This is empirically the most reliable, lowest-token workflow. Docs: https://onsi.github.io/ginkgo/#reporting-and-profiling-suites.
The workflow: one run, JSON-first diagnosis
# One invocation gives you BOTH the human verdict on the terminal AND a structured report.
# --json-report does NOT suppress console output, so you don't pay for two runs.
ginkgo -r -p --no-color --json-report=report.json --output-dir=.ginkgo-report
- Read the terminal tail for the one-line verdict:
FAIL! -- 5 Passed | 6 Failed | 1 Pending | 1 Skipped. Cheap, immediate. - If there are failures, query the JSON with
jq(filters below) to get exactly the failing specs — stable, addressable, order-independent. - Clean up the report dir when done.
Why hybrid and not one or the other:
- Terminal-only is brittle to parse (free-form text) and, under
-p, interleaves failures in nondeterministic order. - JSON-only is wasteful if you dump it: the full
report.jsonis ~9× the tokens of the terminal output. Ajqfailures-only extraction is a fraction of either. The discipline is filter, don't dump.
Where the JSON lands (use --output-dir deliberately)
--json-report=report.jsonalone writesreport.jsonto the current directory — which scatters into package dirs under-rand risks getting committed.- Prefer
--output-dir=DIRto collect everything in one known place (auto-created). With-r, all suites merge into oneDIR/report.json— ideal: one file, one set ofjqfilters. - Use a gitignored or temp location: a repo-local
.ginkgo-report/(add it to.gitignore) or an absolute temp path (--output-dir=/tmp/ginkgo-report). Don't leavereport.jsonin the working tree. --keep-separate-reports(with-r) writes onePACKAGE_report.jsonper package instead of merging — only reach for it when you must attribute failures per package.
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 · 97 lines · 122 tokens per session scan A 22d20c055d43
debugging-failures is a skill published in the GitHub repository onsi/ginkgo (9,066 stars, last pushed 9d ago), licensed MIT. It adds 122 tokens to every session and 1,824 once invoked, about $0.0005 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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