Content
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The content is a well-structured, lean pipeline spec with concrete commands, explicit validation feedback loops, and well-signaled one-level-deep references to real bundle files. It avoids explaining concepts Claude already knows and stays actionable throughout.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and assumes Claude's competence — no concept explanations (e.g., what LaTeX or BibTeX is), each section earns its place with concrete script names, file outputs, and constraints rather than padding. | 3 / 3 |
Actionability | Provides fully executable commands (e.g. `python3 scripts/run_pipeline.py --topic "{主题}" --runs-root runs`) plus a catalog of concrete script names (dedupe_papers.py, select_references.py, validate_counts.py) and exact output file lists — copy-paste ready. | 3 / 3 |
Workflow Clarity | A clearly numbered 0–9 main flow with explicit validation checkpoints in stage 8 (validate_counts.py, validate_review_tex.py, generate_validation_report.py) and hard-constraint feedback rules, matching the anchor's validate→fix→retry pattern for batch operations. | 3 / 3 |
Progressive Disclosure | SKILL.md acts as an overview pointing to one-level-deep, clearly signaled references (ai_scoring_prompt.md, expert-review-writing.md, review-tex-section-templates.md, multilingual-guide.md), all of which exist as real files — no deep nesting. | 3 / 3 |
Total | 12 / 12 Passed |