Content
57%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The content is well-structured and gives a clear interface contract via protocol examples, but it lacks explicit validation checkpoints and delegates the core training logic to an unshown script. Tightening the redundancy between the intro and 'What You Get' and adding a validation gate would raise the score.
Suggestions
Add an explicit validation checkpoint in the workflow (e.g. 'Run validate after export; only deploy when mAP50 meets threshold') with a fix-and-retry loop.
Show or link the actual training invocation rather than only referencing scripts/train.py, so the core action is actionable from the body.
Trim redundancy between the opening paragraph and the 'What You Get' bullets to improve token efficiency.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly lean and avoids explaining concepts Claude already knows, but the 'What You Get' bullets partly restate the intro and the ASCII diagram costs tokens for information also conveyed by the protocol section. | 2 / 3 |
Actionability | Concrete protocol examples (stdin/stdout jsonl) and executable setup commands are present, but the core training action is delegated to an unseen scripts/train.py rather than shown, leaving key guidance incomplete. | 2 / 3 |
Workflow Clarity | The end-to-end sequence (annotate → train → export → deploy) is shown via the diagram and protocol events, but there are no explicit validation checkpoints or error-recovery feedback loops, which the rubric requires for a 3. | 2 / 3 |
Progressive Disclosure | This is a short, single-purpose, self-contained skill with well-organized sections and no nested external reference docs to navigate, so per the simple-skills scoring note it qualifies for a 3 despite having no bundle files. | 3 / 3 |
Total | 9 / 12 Passed |