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multi-factor

Multi-factor cross-sectional stock ranking. Combines factor standardization, equal-weight or IC-weighted scoring, and TopN portfolio construction. Suitable for multi-instrument portfolio strategies.

61

Quality

73%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./a_全网优秀资源/10_大模型/07_skill包/vibe_trading_skills/multi-factor/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

80%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content is lean, well-structured, and actionable with concrete factor and parameter tables, but the batch rebalancing workflow lacks explicit validation checkpoints within the sequenced steps.

Suggestions

Add explicit validation checkpoints to the Signal Logic sequence (e.g. verify >=3 stocks before Z-score normalization, confirm weight normalization sums to 1 after selection).

Include a short executable snippet for Z-score standardization and TopN weight assignment to reach full copy-paste readiness.

Surface the cross-sectional minimum-sample and direction-alignment checks as numbered validation steps rather than only as prose pitfalls.

DimensionReasoningScore

Conciseness

The body is lean and well-sectioned with no padding or explanation of basic concepts (no Z-score or pandas preamble), so every token earns its place.

5 / 5

Actionability

Concrete factor tables with calculation methods/directions and parameter defaults give mostly executable guidance, but the absence of any code or formula snippets leaves minor gaps versus copy-paste readiness.

4 / 5

Workflow Clarity

Signal Logic is a clear numbered 4-step sequence, but as a batch rebalancing operation it lacks explicit validation checkpoints in the workflow; validation appears only as prose pitfalls, so the batch-operation cap applies.

3 / 5

Progressive Disclosure

A short (~52 line) single-purpose skill with no external references and clearly organized sections qualifies for the simple-skill exception, scoring 5 on structure and navigability.

5 / 5

Total

17

/

20

Passed

Description

66%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description concretely states what the skill does and is reasonably distinctive, but it lacks an explicit 'Use when...' trigger clause, leaving the 'when' only weakly implied.

Suggestions

Add an explicit trigger clause, e.g. 'Use when building multi-factor stock ranking portfolios, cross-sectional factor strategies, or TopN selection models.'

Include a few common synonyms (e.g. 'factor model', 'factor investing', 'stock selection') to broaden natural keyword coverage.

Consider mentioning the rebalancing/portfolio-construction outcome more directly to sharpen the 'when' framing.

DimensionReasoningScore

Specificity

Names the domain and lists several concrete actions ('factor standardization, equal-weight or IC-weighted scoring, and TopN portfolio construction'), matching the anchor for several specific actions with minor coverage gaps.

4 / 5

Completeness

The 'what' is clear, but the only 'when' cue is the weak applicability phrase 'Suitable for multi-instrument portfolio strategies' with no explicit 'Use when...' trigger clause, which caps completeness at 3 per the guidelines.

3 / 5

Trigger Term Quality

Natural quant terms like 'multi-factor', 'cross-sectional', 'stock ranking', and 'portfolio construction' are present, but common synonyms such as 'factor model' or 'factor investing' are missing.

4 / 5

Distinctiveness Conflict Risk

'Multi-factor cross-sectional stock ranking' is a specific niche with distinct triggers and minor overlap risk, though not as crisply triggered as the top anchor.

4 / 5

Total

15

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
charliedream1/ai_quant_trade
Reviewed

Table of Contents

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