Content
70%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.
The body is actionable and well-sequenced with explicit validation and recovery, but it is padded with redundant sections and inline boilerplate, and it underuses progressive disclosure for its bundle of helper scripts.
Suggestions
Remove the duplicate "输入" section under 流程 (it repeats the 适用场景/输入 block) and consolidate shared "公共硬约束" boilerplate into a referenced file.
Add brief one-line pointers to the helper scripts (bib_utils, latex_scanner, online_verify, report_utils, runtime_utils) so the bundle structure is navigable.
Externalize the detailed report-format spec into a reference doc and keep SKILL.md as a concise overview.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly task-focused, but it carries redundant duplicate "输入" sections and a lengthy shared "公共硬约束" boilerplate block that could be tightened or externalized. | 3 / 5 |
Actionability | Provides concrete, copy-paste-ready bash commands with full paths and flags for the verified run_ref_alignment.py script, plus explicit output file paths; minor gaps in the JSON schema detail. | 4 / 5 |
Workflow Clarity | Steps 1–4 are clearly sequenced with a dedicated 校验 checklist and a 失败与恢复 feedback loop (retry from the last failed step); validation is present, so the batch-operation cap does not apply. | 5 / 5 |
Progressive Disclosure | Has clear section headers and points to the main script, but the ~150-line body inlines shared boilerplate and never navigates to the five helper scripts; no references/ or assets/ structure exists. | 3 / 5 |
Total | 15 / 20 Passed |