Content
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill is well-structured and actionable with executable code and clear sectioning, but it repeats its core premise and lacks explicit validation checkpoints in its diagnostic workflow.
Suggestions
Collapse the redundant 'When to Apply', 'Identification Checklist', and 'Key Takeaways' sections into a single concise statement of indicators to reduce repetition.
Add an explicit verification checkpoint in the diagnostic steps (e.g. confirm all zero-iteration indicators hold before categorizing as PRE_EXECUTION_FAILURE).
Document or define the expected execution_log dict shape so the provided functions are fully self-contained.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The core premise is restated three times across 'When to Apply', the 'Identification Checklist', and 'Key Takeaways', so while mostly efficient the body could be tightened, matching 'mostly efficient but includes some unnecessary explanation'. | 2 / 3 |
Actionability | Provides executable Python functions (is_zero_iteration_failure, categorize_failure), a concrete checklist, and a routing decision tree that are copy-paste ready, matching the 'fully executable code/commands' anchor. | 3 / 3 |
Workflow Clarity | Diagnostic steps are clearly numbered (Step 1-3) but lack explicit validation checkpoints or feedback loops, fitting 'steps listed but validation gaps; checkpoints missing or implicit' rather than the level-3 anchor requiring validation steps. | 2 / 3 |
Progressive Disclosure | The body is well-organized into clearly labeled sections with no nested or deep references and no bundle files to navigate, so section headers provide clear navigation matching the well-organized level-3 case for a self-contained skill. | 3 / 3 |
Total | 10 / 12 Passed |