Content
75%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 well-crafted, dense skill body: executable forward, inverse, and 2D examples with a training-strategy table, architecture guide, and a pitfalls table that doubles as error-recovery guidance. The main improvements are making each code example self-contained, adding an explicit validation checkpoint in the training workflow, and splitting the worked examples into reference files.
Suggestions
Make examples 2 and 3 standalone by redefining or clearly noting the shared variables (geomtime, bc, ic, alpha) they rely on from example 1.
Add an explicit validation checkpoint after training (e.g., 'check max error; if above tolerance, increase epochs or adjust loss weights and retrain') to close the feedback loop.
Consider moving the three worked examples into references/ files (e.g., examples/heat-inverse.md) with a one-line pointer from SKILL.md to slim the main file.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is efficient: compact 'When to Use'/'Do NOT Use When' lists, three tight code workflows, and dense reference tables with no padding or explanation of concepts Claude already knows. It is not level 5 only because the two-sentence Overview briefly re-explains how PINNs work, which could be trimmed. | 4 / 5 |
Actionability | Three concrete workflows use real, executable DeepXDE API calls (dde.grad.jacobian, TimePDE, FNN, compile/train) with imports, hyperparameters, and evaluation against exact solutions. Not level 5 because examples 2 and 3 depend on variables (geomtime, bc, ic) defined only in example 1, so they are not fully standalone copy-paste ready. | 4 / 5 |
Workflow Clarity | The sequence (PDE definition → geometry → BC/IC → data → network → Adam → L-BFGS → evaluate) is clear and consistently demonstrated, with a phased Training Strategy table and an evaluation step comparing predictions to the exact solution. Not level 5 because validation is implicit (printed errors) rather than an explicit checkpoint with a retrain-on-failure feedback loop. | 4 / 5 |
Progressive Disclosure | A single-file skill with no bundle files, organized into clearly labeled sections (Installation, Core Workflows, Training Strategy, Architecture Guide, Pitfalls) that are easy to navigate. Not level 5 because at ~183 lines some material (e.g., the three worked examples) could be split into one-level-deep reference files to keep SKILL.md as a leaner overview. | 4 / 5 |
Total | 16 / 20 Passed |