Content
82%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.
The body is a tightly written, fully executable fine-tuning recipe with clear sequencing and validation checkpoints plus a genuine one-level reference. Its main gaps are a slightly long inference sanity-check block and an implicit rather than explicit validate→fix→retry recovery loop.
Suggestions
Make the validation feedback loop explicit in step 5 (e.g., 'If gibberish: verify `template: minicpm5`, re-run training, then re-test') to satisfy the destructive/batch validation cap with a clear fix→retry cycle.
Trim the step-5 inference sanity-check snippet to the minimal reproducer, or move the full inference + merge recipes into a referenced file to tighten the SKILL.md overview.
Add a one-line 'Failure modes' note (OOM → reduce batch size / cutoff_len; vLLM clash → separate venv) to convert the implicit recovery hints into an explicit checkpoint.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and assumes Claude's competence (no explanations of fine-tuning/transformers basics), but the step-5 inference sanity-check snippet and the two callout blocks are slightly longer than strictly necessary and could be trimmed. | 4 / 5 |
Actionability | Fully executable end-to-end: install commands, dataset_info.json schema, jsonl format, complete training YAML, train command, multi-GPU flags, validation loss examples, inference code, and merge/full-SFT variants — copy-paste ready and covers the common cases. | 5 / 5 |
Workflow Clarity | Clear numbered sequence (install→register→YAML→train→validate) with explicit checkpoints (loss curve, inference sanity check) and a failure hint, but the validate→fix→retry feedback loop for this batch operation is implied rather than an explicit recovery checklist. | 4 / 5 |
Progressive Disclosure | Well-organized with clear section headers and a single one-level-deep reference link (docs/finetune/llamafactory.md); no bundle files exist, so the monolithic procedural recipe is appropriately inline, though the inference/merge blocks could optionally be split out. | 4 / 5 |
Total | 17 / 20 Passed |