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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.

56

Quality

63%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./agent/src/skills/multi-factor/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

68%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 body is well-structured, concise, and provides mostly executable guidance with a clear numbered workflow and helpful pitfalls table. Its main weaknesses are a missing explicit validation checkpoint for the batch portfolio operation and inlined advanced content that could be split into a reference file.

Suggestions

Add an explicit validation step to the workflow, e.g. after ranking, verify that selected weights sum to 1/N and all others are 0, raising workflow clarity above the batch-operation cap of 3.

Move the Zoo Signal Engine advanced material into a referenced file (e.g. ZOO_ENGINE.md) and keep SKILL.md as an overview with a clear pointer, improving progressive disclosure.

Provide a complete, copy-paste-runnable end-to-end example that constructs the `panel` input before calling `engine.compute_signal(panel)` so the actionability gap is closed.

DimensionReasoningScore

Conciseness

Lean tables and bullet lists dominate the body with little padding; only minor prose like the A-shares aside could be trimmed, fitting the efficient-but-slightly-tightenable anchor.

4 / 5

Actionability

An executable Python snippet with imports and real calls plus a parameter table with defaults gives concrete guidance, but no fully runnable end-to-end example and `engine.compute_signal(panel)` lacks panel setup, leaving minor gaps.

4 / 5

Workflow Clarity

The four-step signal logic is clearly sequenced, but this batch portfolio operation has no explicit validation checkpoint (e.g. verify weights sum to 1/N), capping workflow clarity at 3 per the batch-operation guideline.

3 / 5

Progressive Disclosure

Sections are well-organized with a clear cross-reference to the alpha-zoo skill; the inlined Zoo Signal Engine content that arguably belongs in a separate reference file is the only minor organization gap, and no bundle files are present to verify further.

4 / 5

Total

15

/

20

Passed

Description

58%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 clearly conveys what the skill does with concrete, specific actions, but lacks an explicit "when to use" trigger clause and relies on technical jargon rather than natural user phrasings. It is mostly distinct from sibling skills but could improve trigger coverage and explicit usage guidance.

Suggestions

Add an explicit "Use when..." clause with natural trigger phrases, e.g. "Use when ranking stocks by multiple factors, building a multi-factor portfolio, or composing cross-sectional factor scores."

Include user-natural synonyms such as "rank stocks", "factor strategy", and "portfolio selection" alongside the technical terms to improve trigger quality.

Mention file extensions or concrete artifacts (e.g. panel DataFrames, factor tables) to further sharpen distinctiveness from adjacent strategy skills.

DimensionReasoningScore

Specificity

"Combines factor standardization, equal-weight or IC-weighted scoring, and TopN portfolio construction" names the domain plus several concrete actions, with only minor coverage gaps.

4 / 5

Completeness

The "what" is clearly stated, but there is no explicit "Use when..." trigger clause; "Suitable for multi-instrument portfolio strategies" only weakly implies the when, so completeness is capped at 3 per the guideline.

3 / 5

Trigger Term Quality

Relevant technical terms like "multi-factor", "cross-sectional", "stock ranking", and "TopN portfolio construction" appear, but natural user phrasings (e.g. "rank stocks", "factor strategy") and synonyms are missing.

3 / 5

Distinctiveness Conflict Risk

"Multi-factor cross-sectional stock ranking" carves out a mostly distinct niche, with only minor overlap risk against closely related single-factor or alpha-zoo strategy skills.

4 / 5

Total

14

/

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
HKUDS/Vibe-Trading
Reviewed

Table of Contents

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