Content
70%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 content is a well-sequenced, highly actionable multi-agent research workflow with strong validation checkpoints and feedback loops. Its main weakness is structure: it is a monolithic file with inlined detail rather than an overview pointing to one-level-deep reference files.
Suggestions
Split the inlined Agent prompt template and the financial-data source rules into reference files (e.g. references/agent-prompt.md, references/financial-data.md) and point to them from the main steps.
Trim the explanatory justification paragraphs (e.g. '为什么必须预检') to a single line plus the actionable check, keeping only what Claude cannot infer.
Move the four master-investor framework definitions into a short reference table file so the main workflow stays a lean overview.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly efficient action-oriented prose with concrete commands, but includes justification paragraphs (e.g. the '为什么必须预检' rationale and repeated cautionary notes) that could be trimmed. | 3 / 5 |
Actionability | Provides concrete executable commands (financial_rigor.py, report_audit.py with full flags) and a copy-paste Agent prompt template, with minor gaps from unresolved placeholders and external-file assumptions. | 4 / 5 |
Workflow Clarity | A clear 10-step sequence with explicit validation checkpoints (WebSearch pre-check, financial-rigor verification, data-audit exit-gate) and a re-work feedback loop for a batch multi-agent operation. | 5 / 5 |
Progressive Disclosure | No bundle files exist; all detail (Agent prompt template, financial-data source rules, audit procedure) is inlined in a single ~240-line SKILL.md with section headers but no overview-pointing-to-reference structure. | 3 / 5 |
Total | 15 / 20 Passed |