Content
76%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 highly actionable, well-structured skill with executable examples across the domain. Main gaps are missing validation checkpoints in batch workflows and some inline plotting boilerplate that could be trimmed or externalized.
Suggestions
Add explicit validation checkpoints to batch workflows (e.g., after Lyapunov integration, verify convergence by checking the running exponent has stabilized before reporting).
Trim plotting cosmetics (figsize, fontsize, dpi, grid styling) from code examples to reduce token overhead and keep focus on the analytical logic.
Consider moving the fixed-point classification and bifurcation-type reference tables into a separate reference file to shorten the main SKILL.md body.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly lean with minimal conceptual over-explanation and compact reference tables, but code examples carry plotting cosmetics (figsize, fontsize, dpi, savefig) that are not core to the analysis and could be trimmed. | 4 / 5 |
Actionability | Five fully executable, copy-paste-ready code examples covering phase portraits, fixed points, bifurcations, Lyapunov exponents, and Poincare sections, each self-contained and runnable. | 5 / 5 |
Workflow Clarity | Each workflow is a clear standalone recipe, but batch numerical procedures (bifurcation sweeps, Lyapunov integration) lack explicit in-workflow validation checkpoints; convergence verification appears only in the troubleshooting table rather than as a step. | 3 / 5 |
Progressive Disclosure | Well-organized into clear sections (Overview, When to Use, Core Workflows, reference tables, Troubleshooting) with no nested references, though at ~314 lines some examples or reference tables could be split into bundle files. | 4 / 5 |
Total | 16 / 20 Passed |