Content
81%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 strong, highly actionable pipeline skill: explicit sequencing, validation and fail-closed gates, resume semantics, and real referenced scripts and reference files. Its main cost is length — repeated policy statements and a duplicated reference list could be consolidated to save context.
Suggestions
State the multi-query fail-closed and single-query-fallback rules once (e.g., in 多查询检索) and reference that section from 准备 and 约束 instead of repeating them three times.
Delete or annotate the bare reference list at lines 167–172, since the same files are already listed with purpose in the 准备 section.
Move the operational details of output-directory layout and pipeline_cost.py usage into a reference file (e.g., development-validation-guide.md), keeping SKILL.md to the pipeline itself.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is information-dense with no basic-concept padding, but it is noticeably long and repetitive: the multi-query fail-closed / single-query-fallback rules are restated in the 准备, 多查询检索, and 约束 sections, and the 公共硬约束 block plus the dangling bare list of reference paths (lines 167–172, duplicating the annotated list in 准备) could be consolidated. This fits 'mostly efficient but could be tightened' better than the lean anchor. | 3 / 5 |
Actionability | The bash block gives copy-paste-ready commands for the main entry, two-step prepare/resume flow, explicit single-query fallback, legacy entry, and search-skill-root override, all with real flag names; specifics continue throughout (query JSON schema shapes, 5–25 query bounds, 1–10 scoring, 20–40% high-score distribution, exact script and artifact filenames). All named scripts and reference files exist in the bundle. | 5 / 5 |
Workflow Clarity | The pipeline is explicitly sequenced (准备 → 检索 → 去重 → 评分 → 选文 → 子主题/字数预算 → 写作 → 扩写与验证 → 导出) with validation checkpoints (validate_counts.py, validate_review_tex.py, generate_validation_report.py), fail-closed gates at stage 1, a defined retry path in 失败与恢复, and a feedback loop in 有机扩写与验证 (expand only weak sections, re-validate). | 5 / 5 |
Progressive Disclosure | Detailed prompts and templates are correctly split into references/ one level deep (ai_query_generation_prompt.md, ai_scoring_prompt.md, expert-review-writing.md, review-tex-section-templates.md, multilingual-guide.md — all verified present), and heavy logic lives in scripts/. However, the bare unannotated reference list at lines 167–172 and inlined operational policy (output management, cost tracking) leave minor organization gaps versus the well-signaled ideal. | 4 / 5 |
Total | 17 / 20 Passed |