Content
90%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A high-quality, dense reference body: every explanation is Ginkgo-specific and non-obvious, every code sample is executable, and decision guidance (BeforeSuite vs SynchronizedBeforeSuite table, DB strategy tiers, singleton-collision diagnosis) is concrete. It sits just below top marks on workflow clarity, being organized as a reference rather than a validated step sequence, and on progressive disclosure, where all content is inlined with no bundle files to offload detail into.
Suggestions
Add a short step-sequenced diagnostic workflow (e.g. for auditing a slow parallel run or triaging a parallel-only flake: reproduce with -p → precompile with ginkgo build -r to exclude compile time → check for the flat per-suite ~1s --race gap → identify shared singletons → shard by GinkgoParallelProcess()) with an explicit verify step after each fix, which would raise workflow clarity to a full validation-loop structure.
Move the deep 'What the N processes cost' / --race teardown-cost analysis into a references/ file (e.g. references/performance.md) linked from a two-line summary in SKILL.md, keeping the main file to the flags, mental model, and setup patterns — this would make the inline/offline split fully appropriate and raise progressive disclosure.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and assumes Claude's competence: it explains only Ginkgo-specific, non-obvious mechanics (the separate-process model, the ~1s ThreadSanitizer atexit sleep, the output interceptor hang) and never generic programming concepts. Every section earns its place — the opening line 'Parallelism is where Ginkgo's "every spec is independent" assumption earns its keep' is two clauses doing real orientation work, and there is no padded prose to trim, matching the 'Lean and efficient; every token earns its place' anchor. | 5 / 5 |
Actionability | Guidance is fully executable throughout: runnable bash ('ginkgo -p', '--procs=4', 'GORACE=atexit_sleep_ms=0 ginkgo -r -p --race'), copy-paste-ready Go using real APIs (SynchronizedBeforeSuite with []byte distribution, gexec.Build, GinkgoParallelProcess() port/tmpdir sharding), and a concrete audit command ('precompile with ginkgo build -r'). This matches the score-5 anchor ('Fully executable; copy-paste ready code or commands; specific examples cover the common cases') — nothing is pseudocode. | 5 / 5 |
Workflow Clarity | The material is well-sequenced conceptually (flag → mental model → costs → setup → sharding → integration patterns) and includes diagnostic decision guidance ('Specs that pass in series but fail mysteriously under -p are almost always colliding on a shared singleton... Shard it by process index'), but the skill is reference-style rather than a step-sequenced workflow with explicit validation checkpoints. It fits the score-4 anchor ('Clear sequence with most checkpoints present; minor validation gaps') better than the score-5 anchor, which requires explicit validation steps and feedback loops the parallel-audit and flake-fixing paths only imply. | 4 / 5 |
Progressive Disclosure | Section structure is clear and consistently navigable, with one-level-deep cross-references to sibling skills signaled by '→' (e.g. '→ ginkgo:running', '→ ginkgo:decorators'). However, no bundle files exist (references/, scripts/, assets/ are absent), so the entire ~110-line treatment — including deep diagnostic material like the --race teardown cost analysis — lives inline in SKILL.md; that content could arguably be split out, which fits the score-4 anchor ('Good structure; most content is appropriately placed; minor organization gaps') rather than the score-5 anchor's fully appropriate split. | 4 / 5 |
Total | 18 / 20 Passed |