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.
An actionable, well-sequenced workflow with concrete commands and validation checkpoints for a batch fetch operation. Main weakness is a duplicated config-source section that adds padding without information.
Suggestions
Remove the standalone "配置来源" section — its content is already covered in "Step 0: 读取共享配置", eliminating the duplication.
Tighten the variable list by deleting the trailing "后续统一以共享配置和上面的变量为准" line, which restates the preceding guidance.
Make the multi-day placeholder explicit by showing `--days $DAYS_ARG` directly in the command block instead of the literal N with a separate explanation.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient with concrete commands, but the "配置来源" section duplicates "Step 0: 读取共享配置" (both explain reading user-config.json with local override) and the closing "后续统一以共享配置和上面的变量为准" restates the earlier instruction — tightening would remove noticeable padding. | 3 / 5 |
Actionability | Provides concrete executable bash commands with explicit file paths for both phases (fetch_and_score.py, enrich_papers.py) and documents the two-argument invocation; minor gap is the literal N placeholder that the agent must substitute. | 4 / 5 |
Workflow Clarity | Clear sequence (Step 0 → parse days → Phase 1+2 → Phase 3 → output) with validation checkpoints ("检查输出：确认...存在且包含有效 JSON 数组") and error-recovery notes (HF fallback, weekend strategy); not a full validate→fix→re-run loop, so just below 5. | 4 / 5 |
Progressive Disclosure | Well-organized into labeled sections with clear one-level references to external scripts (fetch_and_score.py, enrich_papers.py, extract_affiliations.py); no in-skill reference files exist, and the inline field/format lists are reasonably placed with only minor bulk. | 4 / 5 |
Total | 15 / 20 Passed |