Content
67%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 prescriptive workflow skill with real scripts and reference files, explicit validation, and thorough failure-recovery guidance. Its main weaknesses are repeated workspace-isolation rules across four sections and generic closing sections (输出/校验) that lack defined pass criteria.
Suggestions
State the `.bensz-api/task-{...}` workspace convention once (e.g., in 输出管理) and reference it elsewhere; the same isolation rules currently appear in 输入与输出, 初始化, 输出管理, and 公共硬约束.
Add an explicit fix-and-re-validate loop after validate_report.py (what to do when validation fails, mirroring the 失败与恢复 style) and define concrete pass criteria in the 校验 section instead of '执行 Skill 已有的静态检查'.
Merge the overlapping 投稿形式要求 and 格式要求 bullets in 调研, and move the 公共硬约束 boilerplate and the detailed 调研 checklists into a reference file to slim SKILL.md into a true overview.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and prescriptive with no concept explanations Claude already knows, but the `.bensz-api/task-...` workspace-isolation rules are stated four times (输入与输出, 初始化, 输出管理, 公共硬约束) and the format-requirements items appear in overlapping bullets in 调研 ("投稿形式要求" vs "格式要求"). This matches 'mostly efficient but includes some unnecessary explanation or could be tightened'; not a 2 because there is no padding or teaching of known concepts, and not a 4 because the repetition is substantive, not minor. | 3 / 5 |
Actionability | Concrete executable commands are provided for both scripts (init_workspace.py with --journal/--cwd/--output-dir, validate_report.py with --report/--journal), sources.json field requirements are enumerated, and named verification sources (SciRev, LetPub, NLM Catalog, DOAJ, Crossref) make the research actionable. It stops short of 5 because commands use placeholder install paths ('/path/to/paper-know-journal/...') and the 成稿 section relies on 'style close to JITC / Cancer Cell samples' without an inline snippet, leaving minor gaps. | 4 / 5 |
Workflow Clarity | The sequence (初始化 → 调研 with sources.json → 成稿 → 验证 via validate_report.py → 输出) is clear, includes an explicit validation script, a required-content checklist, and a dedicated 失败与恢复 section with concrete fallbacks (ISSN/NLM/DOAJ/Crossref cross-check, user confirmation on ambiguity). It is not 5 because the response to validate_report.py failing is implicit (only '验证通过后告知用户' is stated, no fix-and-revalidate loop), and the 输出/校验 sections are generic ('执行 Skill 已有的静态检查...并记录通过标准') without defined pass criteria. | 4 / 5 |
Progressive Disclosure | The body is an overview that delegates detail to real, clearly signaled, one-level-deep references ("资料处理规则见 references/source-policy.md。报告结构见 references/report-template.md" — both files exist and contain no nested references) and to real scripts in scripts/. It is not 5 because the inline 公共硬约束 boilerplate block and the long 调研 checklists are content that arguably belongs in a reference file, and the reference pointers are single easy-to-miss sentences rather than a dedicated navigation section. | 4 / 5 |
Total | 15 / 20 Passed |