Content
85%Weight 40%Scale 1-3Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-structured, actionable detection skill with clear sequencing and good one-level-deep reference usage. The main improvement would be de-duplicating the repeated init/fallback suggestions across steps.
Suggestions
Consolidate the init-stage suggestions (currently repeated in Step 2, Step 3, and Error Handling) into a single canonical location and cross-reference it.
Move the long "Common questions" list in Step 4 into pipeline-map.md so the core status-rendering flow stays uncluttered.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly lean and free of concept-explaining fluff, but the same init suggestions and fallback guidance recur across Step 2, Step 3, and the Error Handling section, which could be tightened. | 2 / 3 |
Actionability | It gives concrete, executable guidance throughout — exact artifact patterns (PROGRESS_TRACKER.json with overallStatus="completed", reports/IMPLEMENTATION_REPORT_*.json, SWIFT_*/SWIFT_REPORT.json) and exact output strings to emit. | 3 / 3 |
Workflow Clarity | The five steps are clearly sequenced with an explicit most-advanced-to-least-advanced detection order (first match wins) and a dedicated Error Handling section covering each failure mode. | 3 / 3 |
Progressive Disclosure | The body is an overview that offloads templates, detection rules, and next-step tables to references/pipeline-map.md via a clearly signaled, one-level-deep path that resolves to a real file. | 3 / 3 |
Total | 11 / 12 Passed |