Content
63%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 a richly detailed, highly actionable multi-step research workflow with concrete search templates, numeric gates, and report formats. Its main weaknesses are length/repetition and a monolithic structure that does not use progressive disclosure to offload detail into reference files.
Suggestions
Move the elaborate report templates and the AI-infrastructure Layer 2-4 teardown example into reference files under references/ (e.g. REPORT-TEMPLATES.md, TEARDOWNS.md) and link to them, reducing SKILL.md to the workflow overview.
Consolidate the repeated valuation guidance into a single authoritative section and cross-reference it from step 6.1 and the core principles instead of restating the red/yellow/green rules three times.
Add an explicit validate→fix→retry loop for the hourly scan (e.g. on missing financial data, fall back to watchlist-only output and log the gap) to strengthen feedback for the batch mode.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body does not explain concepts Claude already knows and is dense with actionable tables and templates, but at ~490 lines it is long and repeats the valuation emphasis across steps 4.2.1, 6.1, and the core principles, so it could be tightened. | 3 / 5 |
Actionability | It provides copy-paste-ready search query templates ('WebSearch "{趋势} supply chain bottleneck 2026"'), concrete numeric thresholds (PS>30x, market cap<$10B), explicit tool commands ('python3 tools/twstock_data.py'), and fill-in report templates, with only minor reliance on judgment for data sourcing. | 4 / 5 |
Workflow Clarity | A clearly sequenced 7-step process with explicit validation gates (trend confirmation ✅/❌, 6-criterion bottleneck rating, mandatory valuation check) and checklists, but it lacks a validate→fix→retry feedback loop for the batch hourly-scan mode. | 4 / 5 |
Progressive Disclosure | Section headers organize the content well, but it is a monolithic ~490-line SKILL.md with no bundle files in references/scripts/assets, and content that could be split out (report templates, the AI-infrastructure teardown example, hourly-scan mode) is fully inlined. | 3 / 5 |
Total | 14 / 20 Passed |