Content
86%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.
A well-structured, highly actionable skill body with concrete commands, clear workflows, and proper one-level-deep references. Main improvement area is trimming redundant restatements across Core Capabilities, Regression Loop, and Rollout Strategy.
Suggestions
Consolidate "Core Capabilities," "Regression Loop," and "Rollout Strategy" so each point lives in one place; reference rather than restate to reduce token redundancy.
Make the validation feedback loop explicit in the Regression Loop (e.g., "if A/B score does not improve or violations appear, revise the candidate and re-run"), turning the implied retry into a spelled-out validate→fix→retry step.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly efficient and free of concept-over-explanation, but "Core Capabilities," the "Regression Loop," and "Rollout Strategy" restate overlapping points and could be tightened; not quite the lean anchor. | 4 / 5 |
Actionability | Provides copy-paste-ready, fully-argued bash commands for both prompt_tester.py (A/B test) and prompt_versioner.py (add/diff/changelog), covering the common cases with concrete flags. | 5 / 5 |
Workflow Clarity | Workflows are clearly sequenced with promotion gates ("Promote only if score and safety constraints improve"), a review checklist, and a regression/feedback loop, but the error-recovery branch on validation failure is implied rather than spelled out. | 4 / 5 |
Progressive Disclosure | SKILL.md serves as a clear overview with a well-signaled References section pointing one level deep to real files (prompt-templates.md, technique-guide.md, evaluation-rubric.md, README.md), each with a description; bundle paths referenced in the body exist. | 5 / 5 |
Total | 18 / 20 Passed |