Content
85%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-structured, actionable skill body with a validated workflow and clean progressive disclosure. The main gap is a few undefined helper symbols in the Python evaluator template that prevent fully copy-paste-ready code.
Suggestions
Define or stub get_kwargs, aggregate_fn, and validate_fn in the Python evaluator template so the example is fully executable as written.
Trim the 'Notes' section, which repeats guidance already covered in 'Conversion Strategy by Language' and the workflow steps.
Consider moving the full Python and non-Python templates into a referenced bundle file so the SKILL.md body stays a lean overview.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Efficient bullet/step structure with no padded concept explanations, though a few Notes and strategy remarks restate earlier guidance and could be trimmed. | 4 / 5 |
Actionability | Provides concrete, mostly executable code templates and a specific smoke-test command, but the evaluator template references undefined helpers (get_kwargs, aggregate_fn, validate_fn) keeping it just short of copy-paste ready. | 4 / 5 |
Workflow Clarity | A clear 9-step sequence with an explicit validation checkpoint (step 8 runs the evaluator and confirms outputs are written) that functions as a feedback loop for this file-generating operation. | 5 / 5 |
Progressive Disclosure | Well-organized overview with clearly signaled, one-level-deep references to verified bundle files (scripts/run_evo.py, scripts/shinka.yaml) and inline templates that are justified as core to the skill. | 5 / 5 |
Total | 18 / 20 Passed |