Content
80%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The content is highly actionable and concise, with clear thresholds, exemptions, and a defined workflow. Its main gaps are the absence of a validation/retry feedback loop for batch screening and no progressive disclosure structure.
Suggestions
Add an explicit validation/retry checkpoint for batch mode, e.g. when data is missing or contradictory, flag it and re-query before scoring, rather than only labeling "数据不足".
Consider moving the detailed output template or the per-indicator methodology into a reference file (e.g. references/output-template.md) to enable progressive disclosure.
For batch mode, add a verification step that cross-checks retrieved financial figures across two sources before applying the exclusion rules.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and table-driven, assumes Claude's competence, and does not explain concepts Claude already knows; every section earns its place. | 3 / 3 |
Actionability | It gives exact indicator thresholds, explicit exemption conditions, a parallel data-collection procedure, and a copy-ready output template — concrete and executable guidance throughout. | 3 / 3 |
Workflow Clarity | The four-step sequence is clear with status markers and exemption checks, but the batch mode lacks an explicit validate→fix→retry feedback loop, which caps batch-operation workflows at 2. | 2 / 3 |
Progressive Disclosure | Sections are well-organized, but the skill is a single monolithic file with no references or content split, so it is not leveraging progressive disclosure. | 2 / 3 |
Total | 10 / 12 Passed |