Content
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is highly actionable with executable code and a well-sequenced workflow including a verification checkpoint, and it cleanly offloads rendering/CI detail to a real one-level reference. It would score higher on conciseness by trimming the narrative Overview and Limitations padding.
Suggestions
Tighten the Overview narrative (the 95% to 60% payment-module story) to a one-line motivation; the table already conveys the axes.
Compress the Limitations bullets into a compact list of constraints rather than explanatory prose.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient and assumes competence, but sections like the Overview's payment-module narrative and the verbose Limitations bullets carry explanatory padding that could be tightened without losing clarity. | 2 / 3 |
Actionability | Provides complete, executable Python functions (detect_falling, detect_stale, detect_orphans) with real thresholds and a copy-paste ready CI YAML workflow, plus concrete shell verification commands. | 3 / 3 |
Workflow Clarity | Six clearly sequenced steps with an explicit verification checkpoint in Step 1 ('assert coverage-history/ exists and holds at least 2 non-empty runs'), and the anti-patterns table supplies error-recovery guidance. | 3 / 3 |
Progressive Disclosure | SKILL.md is a concise overview with detection logic inline; rendering and CI detail are split into one-level-deep, clearly signaled references (references/ledger-rendering-and-ci.md), which exists and is genuinely used. | 3 / 3 |
Total | 11 / 12 Passed |