Content
81%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-engineered instruction-only skill: the pipeline position, input handling, verification workflow, validation checklist, and output contract are all explicit, with genuine feedback loops for unverifiable data and write failures. Weaker spots are mild redundancy (lens lists and rules stated twice) and the absence of any worked example of the target output, which keeps actionability and progressive disclosure just below top marks.
Suggestions
Deduplicate the lens list: state the core-model variables once and have section 4 ('Mechanism analysis') reference them instead of repeating liquidity/interest rates/risk appetite/capital flows/policy/balance sheets a second time.
Add one worked micro-example — e.g., a single filled fact-table row (标签/事实/数值/来源/状态) and one sample 公众号-style title — so the required output format is unambiguous.
Consider moving the 10-section 'Required structure' detail plus the per-lens explanation template into a one-level reference file (e.g., references/output-structure.md) so SKILL.md stays a lean overview.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is instruction-dense with no teaching of known concepts and no filler, e.g. 'If a value cannot be verified, remove it or mark it as 【待】; never build the core judgment on 【待】.' It falls short of anchor 5 due to redundancy: the lens list appears twice (Core model lines 76-83 and section 4 lines 141-146), and 'Analysis rules' partially repeats the 'Validation checklist' items. | 4 / 5 |
Actionability | Guidance is concrete and executable for a writing skill: exact input/output paths ('markdown/daily-finance-YYYY-MM-DD.md', 'markdown/finance-core-analysis-YYYY-MM-DD.md'), a specified fact-table schema ('标签', '事实', '数值', '来源', '状态'), a fixed 10-section output structure, and fallback rules ('If write fails → fallback to chat output'). Not anchor 5 because no worked example is given — e.g., a sample filled fact-table row or one example 公众号 title would make the deliverable unambiguous. | 4 / 5 |
Workflow Clarity | The sequence is clear and gated: locate input (with explicit ambiguity rules for missing/multiple dates), extract the fact table, run external verification with a source hierarchy, analyze, then pass an explicit pre-output 'Validation checklist' covering data correctness, source consistency, logic integrity, and publication readiness. Error-recovery loops are present ('If a value cannot be verified, remove it or mark as 【待】', write-failure fallback), matching the anchor-5 pattern of validation steps plus feedback loops. | 5 / 5 |
Progressive Disclosure | No bundle files exist (references/, scripts/, assets/ are absent), and the body references none, so there are no broken or nested references; sections are well-organized and navigable. It is scored 4 rather than 5 because at ~230 lines the detailed output template (the 10-section 'Required structure' plus per-lens requirements) is inline content that could be split into a one-level reference file, keeping SKILL.md as a leaner overview. | 4 / 5 |
Total | 17 / 20 Passed |