Content
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The content is strong on actionability and progressive disclosure, with real executable scripts and well-organized one-level-deep references, but it is held back by missing validation checkpoints for its batch video-generation workflow and minor redundancy in the setup section.
Suggestions
Add explicit validation/verification checkpoints after key batch steps (e.g., verify generated slide count and brand_style.json validity before synthesis, with a fix-and-retry loop on failure).
Remove the duplicated dependency list in 前置准备 since it already appears in the frontmatter, or reference it instead of restating.
Add an error-recovery checklist for video synthesis failures (missing assets, FFmpeg errors, audio/subtitle sync mismatches).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient with bullets and executable blocks and no basic-concept explanation, but it repeats the dependency list from the frontmatter in 前置准备 and some role steps are slightly padded, so it could be tightened. | 2 / 3 |
Actionability | Provides fully executable, copy-paste-ready bash commands invoking real scripts (audio_processor.py, subtitle_generator.py, roadshow_composer.py) with concrete flags, matching the anchor for executable code. | 3 / 3 |
Workflow Clarity | The ten-role sequence is clear with outputs feeding the next step, but batch operations (15-100 page generation, video synthesis) lack any validation/verification checkpoints or error-recovery loops, which caps workflow_clarity at 2 per the rubric. | 2 / 3 |
Progressive Disclosure | Clear overview in SKILL.md with a well-signaled 资源索引 pointing one level deep to real reference and script files (all verified to exist), with content appropriately split into separate reference files and no nested references. | 3 / 3 |
Total | 10 / 12 Passed |