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correlation-analysis

Correlation and cointegration analysis — co-movement discovery, deep return-correlation analysis, sector clustering, realized correlation, Engle-Granger / Johansen cointegration, half-life, Kalman dynamic hedge ratio, cross-market linkage analysis, and pair-trading signal generation

65

Quality

80%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

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

Quality

Content

77%

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

A highly actionable, well-sequenced skill with executable code and strong validation checkpoints, but it is a long monolithic document that could be split into reference files and trimmed of explanatory prose to improve token efficiency and progressive disclosure.

Suggestions

Split the large reference material (e.g. the empirical cross-market tables and full function libraries) into one-level-deep reference files (e.g. REFERENCES.md, CROSS_MARKET.md) and link them from a concise overview.

Remove conceptual explanations Claude already knows (e.g. the definition of correlation vs cointegration) to reduce token load and lift conciseness.

Add explicit 'See X.md' navigation pointers so the SKILL.md overview points clearly to the detailed sections rather than inlining everything.

DimensionReasoningScore

Conciseness

The body is mostly efficient and packed with useful empirical tables, but at ~1100 lines it includes explanatory prose Claude largely knows (e.g. 'Correlation measures the degree of co-movement. Cointegration measures whether a long-run equilibrium relationship exists') and could be tightened, so it is not a 3.

2 / 3

Actionability

It provides many complete, executable Python functions with docstrings, concrete thresholds, and a full output-format template — copy-paste ready guidance rather than pseudocode, matching the 'fully executable code' anchor.

3 / 3

Workflow Clarity

The 'Full Workflow From Correlation to Signal' lays out Steps 1–5 with explicit validation/monitoring checkpoints (re-run cointegration monthly, warn if half-life exceeds 2×, out-of-sample validation, spread-health scoring), fitting the 'clear sequence with explicit validation steps' anchor.

3 / 3

Progressive Disclosure

Content is well-sectioned into modes but entirely inline in one ~1100-line monolithic SKILL.md with no separate reference files or one-level-deep pointers; the 'content that should be separate is inline' and no-references-present pattern fits the score-2 anchor, and it is far over the 50-line simple-skill threshold.

2 / 3

Total

10

/

12

Passed

Description

82%

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

A richly specific, well-differentiated description that names many concrete capabilities and natural domain triggers, but it omits an explicit 'Use when...' usage clause, which caps its completeness.

Suggestions

Append an explicit 'Use when...' clause, e.g. 'Use when analyzing asset co-movement, testing for long-run equilibrium between price series, or building pair-trading signals.'

Keep the concrete capability list but consider trimming the most jargon-heavy terms (e.g. 'Kalman dynamic hedge ratio') into more user-natural phrasing.

DimensionReasoningScore

Specificity

The description enumerates many concrete analyses — 'co-movement discovery, deep return-correlation analysis, sector clustering, realized correlation, Engle-Granger / Johansen cointegration, half-life, Kalman dynamic hedge ratio, cross-market linkage analysis, and pair-trading signal generation' — matching the 'lists multiple specific concrete actions' anchor.

3 / 3

Completeness

It thoroughly answers 'what' but provides no explicit 'Use when...' trigger clause, and the rubric guideline caps completeness at 2 when such trigger guidance is missing, so it is not a 3.

2 / 3

Trigger Term Quality

It uses natural domain terms a quant practitioner would say ('correlation', 'cointegration', 'pair-trading', 'hedge ratio', 'half-life') with good coverage rather than generic jargon, fitting the 'good coverage of natural terms' anchor.

3 / 3

Distinctiveness Conflict Risk

'Correlation and cointegration analysis' carves a clear, specialized quant niche with distinctive triggers unlikely to fire for unrelated skills.

3 / 3

Total

11

/

12

Passed

Validation

87%

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

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (1103 lines); consider splitting into references/ and linking

Warning

frontmatter_unknown_keys

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

Warning

Total

14

/

16

Passed

Repository
charliedream1/ai_quant_trade
Reviewed

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