Content
71%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.
A well-sequenced, actionable analytical skill with concrete quantitative guidance and a clear output template. Its main weakness is progressive disclosure: a reference file exists but is never invoked from the body, and the content is denser than it needs to be.
Suggestions
In Step 4 (前瞻性关键问题拆解), explicitly link to references/advanced-frameworks.md (e.g. '科技/AI/Robotaxi 公司参见 advanced-frameworks.md') so the bundled reference is actually discovered and used.
Tighten Step 2's eight-pitfall section by collapsing the four 隐蔽 pits into a single condensed table or moving detailed thresholds into the reference file, reducing token load.
Add a brief validation checkpoint after Step 2 (e.g. '确认八大坑位均已给出 ✅/⚠️/🚨 结论后再进入估值') to turn the implicit scan into an explicit validate-before-proceed loop.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient and well-structured with purposeful tables and checklists, though the eight-pitfall and key-question sections run long and could be tightened in places without losing substance. | 4 / 5 |
Actionability | Provides concrete quantitative thresholds (OCF/净利润 >1, 商誉/净资产 >30%, 其他应收款/总资产 >5%) plus specific file-naming and mkdir commands, with only minor gaps where analytical judgment is left underspecified. | 4 / 5 |
Workflow Clarity | A clear eight-step sequence (Step 0–7) with explicit per-pitfall conclusion labels (✅/⚠️/🚨), though it lacks a rigorous validate→fix→retry feedback loop for the risk-scan and output-writing steps. | 4 / 5 |
Progressive Disclosure | A one-level-deep reference (advanced-frameworks.md) exists, but the body never signals or links to it in the workflow, leaving the main content somewhat monolithic and the reference effectively disconnected. | 3 / 5 |
Total | 15 / 20 Passed |