Content
57%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 highly actionable with executable code and concrete schemas, but it is over-long and monolithic. Splitting the example report, algorithms, and data structures into referenced files and tightening the example output would materially improve conciseness and progressive disclosure.
Suggestions
Move the full example report, the algorithm code blocks, and the data-structure JSON into separate reference files (e.g. references/report-template.md, references/algorithms.py, references/data-schema.json) and link to them from the body.
Add an explicit validation/danger-signal checkpoint into the workflow (e.g. 'Step 3.5: run 危险信号检测 before generating recommendations; escalate Level 3 items to medical disclaimer') so checkpoints are wired into the sequence rather than described separately.
Trim the 220-line example report to a compact skeleton plus one fully-worked nutrient, cutting the ASCII trend art and redundant tables to recover token budget.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Executable code, JSON schemas, and algorithms earn their place, but the ~220-line full example report (with ASCII trend art) and exhaustive vitamin/mineral enumerations are padding that could be trimmed or externalized. | 3 / 5 |
Actionability | Provides concrete, mostly copy-paste-ready Python (calculate_rda_achievement, nutrient density, HEI), explicit data-source file paths, and a JSON schema; minor gaps such as the undefined RDA dict and meal_data fields keep it just below 5. | 4 / 5 |
Workflow Clarity | A clear four-step sequence (确定范围→读取数据→数据分析→生成报告) exists, and safety mechanisms (危险信号检测, 建议分级) are present, but they are not wired into the workflow as explicit validation checkpoints. | 3 / 5 |
Progressive Disclosure | No bundle files exist and the body is a single ~770-line monolith; the example report, algorithm library, and data-structure reference clearly belong in separate one-level-deep reference files. | 3 / 5 |
Total | 13 / 20 Passed |