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.
A dense, highly actionable reference of neural-PDE training patterns with executable code and useful decision/pitfall tables. It is concise and well-structured; the main opportunity is adding an explicit validation/feedback loop around the autoregressive training step and optionally splitting the longer formula blocks into a reference file.
Suggestions
Add an explicit validation checkpoint inside the rollout-training loop (e.g. 'evaluate val nRMSE every N epochs; if it diverges, reduce NOISE_STD / shorten rollout horizon') to close the workflow_clarity gap for a batch/iterative operation.
Consider moving the full nRMSE and multi-component loss implementations into a references/ file, keeping SKILL.md as an overview with the decision table and key snippets, to improve progressive_disclosure given the 187-line body.
Trim a few redundant inline code comments (e.g. '# Always sees perfect input', '# Shift window, append prediction') that restate the surrounding prose, to nudge conciseness toward fully lean.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and assumes competence (no basic-concept padding); prose like 'The single biggest mistake ...' and the nRMSE WARNING earn their place as domain-specific insight, though a few framing sentences and inline comments could still be trimmed. | 4 / 5 |
Actionability | Provides fully executable, copy-paste-ready functions (h1_loss, frequency_loss, calc_nrmse_pertimestep, calc_nrmse_frobenius, denormalize) plus specific hyperparameter values (NOISE_STD, loss weights) and a problem-type decision table covering the common cases. | 5 / 5 |
Workflow Clarity | The Train/Val/Test split gives a clear sequenced workflow with checkpoints (val for selection, test evaluated ONCE), the nRMSE section requires verifying against both formulas, and the Common Pitfalls table supplies error-recovery guidance; minor validation gaps remain in the rollout-training loop itself. | 4 / 5 |
Progressive Disclosure | Well-organized with clear section headers and no nested references; content is self-contained and cohesive. At ~187 lines it exceeds the 50-line simple-skill threshold, so a couple of the longer reference-style blocks (detailed loss/metric implementations) could optionally be split out, but the current single-level structure is navigable. | 4 / 5 |
Total | 17 / 20 Passed |