Content
68%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 an efficient, mostly executable four-step pandas workflow with clear sequencing and a well-signaled parent reference. Its main weakness is the absence of validation/verification checkpoints for a batch export operation, which caps workflow clarity.
Suggestions
Add a validation checkpoint after filtering/export, e.g. assert the output row count matches the filtered count and verify the file was written before reporting success.
Replace hardcoded 'input_data.xlsx' and 'Sheet1' with guidance to derive them from the user's request, and document how to handle missing numeric columns gracefully.
Make the placeholder column-name logic (currently commented out) explicit or remove it to avoid ambiguity about what to execute.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dominated by executable code with brief step descriptions and minimal padding; only a few inline comments like '# 读取目标数据表' could be trimmed. | 4 / 5 |
Actionability | Provides concrete, copy-paste-ready pandas code covering the common case (filtering val_a/val_b/val_c == 0 and exporting), though paths and sheet/column names are hardcoded placeholders. | 4 / 5 |
Workflow Clarity | Four steps are clearly sequenced (Step1–Step4), but this batch/export operation has no validation or verification checkpoints, capping workflow clarity at 3 per the rubric. | 3 / 5 |
Progressive Disclosure | Content is organized into clearly labeled steps with a single one-level reference to the parent workflow SKILL.md and no nested references; minor organization gaps only. | 4 / 5 |
Total | 15 / 20 Passed |