Content
32%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.
The body is concise and section-organized but provides almost no actionable, executable guidance and relies on a reference file that does not exist in the bundle. It reads as generic boilerplate rather than a skill-specific playbook.
Suggestions
Replace abstract instructions with concrete, copy-paste-ready pytest examples (fixture definition, mocking with monkeypatch/pytest-mock, parametrize) covering the common cases.
Create the referenced resources/implementation-playbook.md (and the resources/ directory) or remove the dangling reference so progressive disclosure actually resolves.
Add an explicit workflow with validation checkpoints — e.g., run pytest, read failures, fix, re-run until green — instead of the generic 'apply best practices and validate outcomes'.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and does not explain concepts Claude already knows, but the boilerplate instruction bullets ('Apply relevant best practices', 'Provide actionable steps and verification') add little signal and could be trimmed. | 4 / 5 |
Actionability | The instructions are entirely abstract — 'Clarify goals, constraints, and required inputs', 'Apply relevant best practices and validate outcomes' — with no concrete code, commands, or specific pytest patterns; it describes rather than instructs. | 1 / 5 |
Workflow Clarity | A rough generic sequence exists (clarify goals → apply best practices → verify) but it has many gaps and no concrete validation checkpoints; 'validate outcomes' is unspecified. | 2 / 5 |
Progressive Disclosure | The body points to 'resources/implementation-playbook.md' for detailed patterns, but no resources/ directory or file exists in the bundle, so the one-level-deep reference is broken and navigation fails. | 2 / 5 |
Total | 9 / 20 Passed |