Content
52%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 delivers genuinely actionable, domain-specific guidance — a fully specified risk-scoring algorithm, concrete data sources, and detailed output structure — but it is a monolithic 980-line document. The full report template and six example outputs should live in reference files, and the triplicated crisis/emergency content should be consolidated. It reads as a spec dump rather than a lean operating manual.
Suggestions
Split the ~280-line report template and the six worked examples into reference files (e.g. references/report-template.md, references/examples.md), keeping SKILL.md as a lean overview with clearly signaled one-level-deep links.
De-duplicate the crisis content: the risk-scoring algorithm, risk-factor table, and emergency resources each appear three times (step 5, output template, example 3) — state the algorithm once and reference it elsewhere.
Specify the computational methods the body gestures at (how to compute correlation coefficients, how to '预测未来趋势', expected JSON schemas for the data files), or point to a reference containing them, to close the actionability gaps.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The ~980-line body is noticeably padded: a ~280-line placeholder report template, six fully worked example outputs, and significant duplication — the crisis risk scoring, risk-factor table, and emergency resources each appear three times (algorithm section, output template, and example 3). Not 1 because it avoids explaining concepts Claude already knows (content is domain-specific algorithms), but well below efficient. | 2 / 5 |
Actionability | Highly concrete for an instruction-only skill: exact data file paths, a fully numeric 0-20 crisis risk scoring algorithm with per-factor thresholds, severity cutoffs (5/10/15), explicit escalation timelines, error-handling branches, and realistic example outputs. Not 5: methods for computing correlation coefficients (r), trend prediction, and the data schemas are left unspecified; not 3 because the guidance is directly executable, not pseudocode. | 4 / 5 |
Workflow Clarity | Ten clearly numbered steps (数据读取 → ... → 生成报告) with an explicit input-validation step (file existence, structure, minimum data points), a dedicated error-handling section, and the crisis step flagged highest priority. Read-only analysis, so no destructive/batch cap applies. Not 5: no validate→fix→retry loop for malformed or partial data mid-analysis; validation is front-loaded only. | 4 / 5 |
Progressive Disclosure | No bundle files exist (references/, scripts/, assets/ are absent) and ~600 lines of report template and worked examples that clearly belong in separate reference files are inlined in SKILL.md. Section headers are good, but there is zero file-level disclosure or navigation — the anchor 'content that clearly belongs in separate files is inlined' applies directly. Not 3: no references exist at all to be 'not clearly signaled'; not 1: the body itself is well sectioned and navigable. | 2 / 5 |
Total | 12 / 20 Passed |