Content
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is a tightly written, highly actionable reviewer persona that assumes competence and adds only non-obvious editorial judgment. It pairs concrete finding taxonomies with explicit calibration and suppression rules, leaving little wasted token budget.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and assumes Claude's competence, covering only what a technical editor needs ('What you're hunting for', 'Confidence calibration', 'What you don't flag') with no padding or basic-concept explanations. | 3 / 3 |
Actionability | Concrete, executable guidance throughout: named finding categories with worked examples, numeric confidence thresholds (0.80+, 0.60-0.79, below 0.50 suppress), and explicit output directives like 'Flag with autofix_class: auto and group by logical theme, keeping original R# IDs'. | 3 / 3 |
Workflow Clarity | It is a single unambiguous review task, which the simple-skill note allows to score 3, and the confidence-calibration block acts as an explicit gating checkpoint (suppress below 0.50) before emitting findings. | 3 / 3 |
Progressive Disclosure | Under 50 lines with no bundle files and no need for external references, yet well-organized into clear sections, satisfying the short-skill progressive-disclosure criterion. | 3 / 3 |
Total | 12 / 12 Passed |