Content
92%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a high-quality skill that provides concrete, actionable guidance for generating custom mutation operators. It excels at actionability with real code examples and workflow clarity with explicit validation criteria. The content is appropriately dense without unnecessary explanation, though the length suggests some content could be split into reference files.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is dense with actionable information and avoids explaining concepts Claude already knows. Tables are used efficiently to convey comparisons, and every section adds unique value without padding. | 3 / 3 |
Actionability | Provides fully executable code examples (mutmut_config.py with real Python), specific bash commands for mining bug history, and concrete operator patterns. The implementation section is copy-paste ready. | 3 / 3 |
Workflow Clarity | Clear multi-step process: mine bugs → identify inverse patterns → implement operators → validate with 4 explicit criteria → dry run → adopt. The validation section provides explicit checkpoints before adding operators permanently. | 3 / 3 |
Progressive Disclosure | Content is well-organized with clear sections and tables, but it's a substantial monolithic document (~150 lines). The domain-specific operator catalog and implementation details could potentially be split into separate reference files for better navigation. | 2 / 3 |
Total | 11 / 12 Passed |