ci

Configure Ginkgo for continuous integration — the recommended CLI flag set and the rationale for each flag (-r -p --randomize-all --randomize-suites --fail-on-pending --fail-on-empty --keep-going --cover --race --trace --json-report --timeout --poll-progress-after/-interval), invoking via go run to pin the CLI to go.mod, the exit-code safeguards that catch committed Focus/Pending and empty filters, collecting report and coverage artifacts with --output-dir, and CI-friendly output (--github-output/--force-newlines/--no-color). Use when setting up or hardening a CI pipeline for a Ginkgo suite.

Quality

95%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

Quality

Content

100%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A tight, executable CI guide: copy-paste invocation, per-flag rationale, explicit safeguards as validation checkpoints, and clean cross-skill navigation. Concise, actionable, and well-structured with no wasted tokens.

Dimension	Reasoning	Score
Conciseness	Lean and efficient throughout — no padding or explanation of what Ginkgo/libraries are; every section ('maximize signal', 'Collect, don't bail') earns its place and assumes Claude's competence.	5 / 5
Actionability	Provides a copy-paste-ready `go run` invocation, a per-flag rationale table, and concrete value suggestions (e.g. '120s/30s are reasonable'); the guidance is fully executable.	5 / 5
Workflow Clarity	Clear sequenced guidance with explicit validation emphasis — the 'exit-code safeguards' section, 'Collect, don't bail', and the caution against '--fail-fast' and '--flake-attempts' act as feedback-loop checkpoints for a batch CI operation.	5 / 5
Progressive Disclosure	Well-organized sections with one-level-deep cross-skill references ('ginkgo:running', 'ginkgo:reporting') and a single external rationale link; no bundle files exist, so the structure is appropriately self-contained and easy to navigate.	5 / 5
	Total	20 / 20 Passed

Description

90%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A dense, specific, third-person description that concretely names capabilities and provides an explicit 'Use when' trigger tied to a distinct Ginkgo CI niche. Slightly keyword-thin on plain synonyms, but otherwise strong.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'the recommended CLI flag set', 'invoking via go run to pin the CLI to go.mod', 'the exit-code safeguards that catch committed Focus/Pending and empty filters', 'collecting report and coverage artifacts with --output-dir', and 'CI-friendly output' — giving comprehensive coverage of the skill's capabilities.	5 / 5
Completeness	Both 'what' (configure flags, pin via go run, enforce safeguards, collect artifacts) and 'when' ('Use when setting up or hardening a CI pipeline for a Ginkgo suite') are explicitly and concretely answered.	5 / 5
Trigger Term Quality	Natural terms like 'setting up or hardening a CI pipeline', 'CI pipeline', and 'Ginkgo suite' appear, but coverage leans technical (flag names) and misses some common synonyms a user might say.	4 / 5
Distinctiveness Conflict Risk	The Ginkgo-specific CI niche with distinct triggers ('hardening a CI pipeline for a Ginkgo suite') makes conflict with other skills minimal.	5 / 5
	Total	19 / 20 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: onsi/ginkgo
Path: plugins/ginkgo/skills/ci/SKILL.md
Commit: f2d0f65

Reviewed: 10 days ago

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