Content
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
Highly actionable content with excellent progressive disclosure and well-sequenced checklists. The main gaps are mild verbosity from restating the description and explaining known concepts, and implicit rather than explicit validation gates within the training workflows.
Suggestions
Remove the restated description in Quick start and the explanatory line about what expert parallelism does; assume Claude's competence to tighten conciseness.
Add explicit validation gates to the training workflows (e.g., 'If MFU < 40% or memory > 80GB, do not proceed; return to Step 3 to tune parallelism/micro-batch') so checkpoints are pass/fail rather than monitoring-only.
Fold the parallelism 'rules of thumb' that overlap with the config table into the references to reduce inline repetition.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly efficient and concrete, but it repeats the frontmatter description in the Quick start, explains concepts Claude already knows ('Expert parallelism distributes different experts across GPUs, reducing memory while maintaining capacity'), and could be tightened; it is not a 1 because it is dense with real commands and configs rather than vague prose. | 2 / 3 |
Actionability | Provides fully executable bash scripts and torchrun commands with specific flags, concrete parallelism config tables, and copy-paste-ready fix snippets, matching the 'fully executable code/commands; copy-paste ready' anchor. | 3 / 3 |
Workflow Clarity | Workflows use clear numbered checklists and a monitoring step with target thresholds, plus a troubleshooting section for error recovery, but validation within workflows is monitoring-style and implicit rather than explicit pass/fail gates; for expensive batch training the rubric caps this at 2 without explicit validation checkpoints. | 2 / 3 |
Progressive Disclosure | The body is a clear overview that signals four real, one-level-deep reference files (parallelism-guide.md, benchmarks.md, production-examples.md, training-recipes.md) with descriptive labels, keeping advanced detail out of SKILL.md. | 3 / 3 |
Total | 10 / 12 Passed |