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 well-structured, actionable skill body with executable code, a validation table, and concrete commands across a clear workflow. Minor gains are possible by adding an explicit test/analysis failure-recovery loop and trimming light padding.
Suggestions
Add a feedback loop after the test and analysis steps (e.g., 'If tests or analysis fail, fix the issue and re-run until clean') to make the workflow's validation explicit.
Tighten light padding such as 'As appropriate, multiple validations can be completed. Complete the less specific ones first, such as not being blank.' into a more direct rule.
Consider whether the 'Use the data model from a page' section belongs inline or would be better as a clearly signaled one-level reference, since it is tangential to model creation.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Largely lean with a complete code template, validation table, and concrete commands; only minor instances of padding such as 'As appropriate, multiple validations can be completed' could be trimmed. | 4 / 5 |
Actionability | Provides a fully executable Dart model template, concrete validation helper signatures in a table, and copy-paste commands for codegen, tests, and analysis covering the common cases. | 5 / 5 |
Workflow Clarity | Clear numbered sequence (read existing → write model → run build_runner → add tests → run tests → run analyze) with verify checkpoints, but lacks an explicit error-recovery feedback loop. | 4 / 5 |
Progressive Disclosure | Well-organized into clear sections with content appropriately inline for a cohesive guide and no nested references, though at over 170 lines the page-usage section is mildly tangential. | 4 / 5 |
Total | 17 / 20 Passed |