Content
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is concise and well-organized into three executable steps, but the code is not fully copy-paste ready (placeholders and undefined variables) and the workflow lacks validation checkpoints for its batch/output operations.
Suggestions
Replace placeholders and undefined variables (target_sheet, os, df) with concrete setup or clearly marked substitution so the code is copy-paste executable.
Add a validation/checkpoint step between processing and output (e.g., verify the cleaned column is non-empty and confirm the target column matched before writing the file).
Include the missing imports (os, pandas as pd) and a minimal df/sheet-loading preamble so each step runs standalone.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean code blocks with a one-line scoping note and brief inline comments; no padding or explanation of concepts Claude already knows, so every token earns its place. | 3 / 3 |
Actionability | Real Python is provided, but it includes placeholders ('目标清洗列' 占位示例) and undefined references (target_sheet, os, df), so it is not copy-paste executable without missing setup context. | 2 / 3 |
Workflow Clarity | Three steps are clearly sequenced (Step1/Step2/Step3), but there are no validation checkpoints for the batch statistics and file-write operations, which per the guidelines caps workflow clarity at 2. | 2 / 3 |
Progressive Disclosure | A compact, single-purpose skill under 50 lines organized into well-separated Step1/Step2/Step3 sections with no need for external references, satisfying the simple-skill exception for a score of 3. | 3 / 3 |
Total | 10 / 12 Passed |