Content
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The content is highly actionable with a clear, checkpointed workflow and clean section organization. Its main weakness is conciseness: explanatory commentary and large inline code blocks could be trimmed or split out.
Suggestions
Move the large inline W&B Python snippets and the Modal/Vast/Feishu branches into reference files (e.g. references/wandb.md), keeping only the core screen/SSH workflow in SKILL.md.
Trim the opening cadence blockquote and the "What to extract" prose to essentials, since Claude can infer what training-loss/eval-metric signals mean.
Fix or remove the dangling reference to ../shared-references/external-cadence.md, which does not resolve to a real file.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly lean executable commands, but the opening cadence blockquote, the verbose "What to extract" commentary, and the large inline W&B Python blocks add tokens Claude could do without or that could be referenced out. | 2 / 3 |
Actionability | Provides copy-paste-ready commands (ssh screen -ls, hardcopy, vastai show instances, modal app logs) and complete W&B API Python snippets, matching the fully-executable anchor. | 3 / 3 |
Workflow Clarity | A clear numbered Steps 1-6 sequence with conditional checkpoints ("If hardcopy fails...", "If JSON results exist...") and error-handling notes; monitoring is non-destructive so no destructive-loop cap applies. | 3 / 3 |
Progressive Disclosure | No bundle files exist; the self-contained body is organized into well-labeled sections with one-level-deep signaled references, satisfying the simple-skill note. A broken external link (shared-references/external-cadence.md) is a minor defect not captured by the bundle-structure anchors. | 3 / 3 |
Total | 11 / 12 Passed |