Content
100%Weight 40%Scale 1-3Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-crafted, highly actionable debugging skill: concise and competence-assuming, with concrete code/commands, an explicit validate-and-narrow feedback loop, and clean section organization. The main minor weakness is light repetition of the 'do not commit' hygiene reminder across sections.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is information-dense and assumes Claude's competence (no explanations of what MLX, PyTorch, or diffusers are); every section earns its place, though the 'do not commit unless asked' reminder repeats a few times. | 3 / 3 |
Actionability | Provides concrete, executable guidance — real commands (uv run python, np.savez, torch.save, /usr/bin/time -p), a complete runnable Python block, and exact tolerance starting points (atol=1e-5/1e-2) — copy-paste ready. | 3 / 3 |
Workflow Clarity | Clear sequenced workflow (steps 1-4) with explicit validation feedback loops ('If a checkpoint fails: add an earlier checkpoint and repeat') and a results-interpretation table, plus a dedicated inject-latents procedure with its own Step 1/Step 2. | 3 / 3 |
Progressive Disclosure | A self-contained single SKILL.md with well-organized sections and named cross-links to sibling skills (mflux-model-porting, mflux-testing); no external bundle files are needed, so the simple-skill note allows a top score for clear organization. | 3 / 3 |
Total | 12 / 12 Passed |