Content
100%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.
The body is a well-structured, highly actionable operational guide with an explicit workflow, validation feedback loop, and properly split one-level-deep references. It earns top marks; the only minor trim opportunity is the color-extraction explanatory prose.
Suggestions
Tighten the 卡身强调色 prose about manual color adjustment into a short bullet list of the two exception cases rather than a paragraph.
Consider promoting the most common Gotchas (封面 s_→t7_, avatar thumb trap) into the 流程 steps inline so the critical pitfalls sit next to the actions that trigger them.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is operational and dense rather than padded with concepts Claude already knows — no basic explanations of libraries, cards, or generation — and the Gotchas list is high-signal, though the color-extraction prose could be tightened slightly. | 3 / 3 |
Actionability | Fully executable guidance throughout: exact curl calls with headers/payloads, python3 invocations with argument examples, a node render command, and a template-variable table — copy-paste ready. | 3 / 3 |
Workflow Clarity | A clear 9-step sequence is laid out with an explicit validation checkpoint (Read the rendered PNG and verify by eye) and a regenerate feedback loop, plus a delivery self-check checklist against visual.md. | 3 / 3 |
Progressive Disclosure | SKILL.md is an overview pointing to one-level-deep references (extraction.md, visual.md) and assets, each signaled with a one-line description of its contents; all referenced bundle files (gen_illustration.py, extract_color.py, library_template.html, ljg-portrait.png, extraction.md, visual.md) exist. | 3 / 3 |
Total | 12 / 12 Passed |