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strategy-generate

Create, modify, and optimize quantitative trading strategies, then backtest and evaluate them.

61

Quality

73%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./agent/src/skills/strategy-generate/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

85%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 highly actionable with a clear, validated workflow and executable contract details — its strongest dimensions. The main weakness is progressive disclosure: substantial reference-grade material is inlined rather than split into one-level-deep reference files.

Suggestions

Move the detailed config.json field reference and Review Criteria into separate files (e.g. CONFIG.md, REVIEW.md) with clearly signaled links, keeping SKILL.md an overview.

Surface the existing examples.md and cross-market-strategy reference earlier in the body where the relevant topics are introduced.

Consider extracting the Instrument Code Normalization and Market Detection tables into a reference file to reduce inline bulk.

DimensionReasoningScore

Conciseness

The body is action-oriented and free of padded explanations of basic concepts; a few dense sections (position_adjustment, rebalance_tolerance) include extra measured detail that could be trimmed but mostly earns its place.

4 / 5

Actionability

Provides an executable SignalEngine contract with exact signature and return semantics, a complete config.json schema, regex-based normalization rules, and a runnable syntax-check command — copy-paste ready guidance for common cases.

5 / 5

Workflow Clarity

A clear 7-step numbered workflow includes an explicit syntax-check validation step and an iterative fix→backtest→re-evaluate feedback loop, plus hard gates and bug categories for evaluation.

5 / 5

Progressive Disclosure

Structure and section headers are good, but nearly all reference-worthy detail (config.json field docs, review criteria, normalization rules) is inlined; only one local reference (examples.md) plus one cross-skill link exist, so the overview is not clearly separated from deeper material.

3 / 5

Total

17

/

20

Passed

Description

62%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 is specific and well-scoped to a distinct niche, with several concrete actions and good conflict resistance. Its main weakness is the absence of any explicit 'Use when...' trigger guidance, which caps completeness and limits activation quality.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user wants to build, backtest, or optimize a quantitative trading strategy.'

Include natural synonyms users actually say, such as 'quant strategies', 'algo trading', or 'systematic trading'.

Optionally mention the configurable markets (stocks, crypto) to broaden trigger coverage without losing distinctiveness.

DimensionReasoningScore

Specificity

Lists several concrete actions — 'Create, modify, and optimize quantitative trading strategies, then backtest and evaluate them' — covering a clear action set within one domain, with only minor coverage gaps.

4 / 5

Completeness

It clearly states what the skill does but provides no 'Use when...' clause or equivalent trigger guidance; per the rubric, a missing explicit trigger clause caps completeness at 3.

3 / 5

Trigger Term Quality

Relevant keywords like 'quantitative trading strategies', 'backtest', and 'evaluate' are present, but common synonyms users might say ('quant strategies', 'algo trading', 'systematic trading') are missing.

3 / 5

Distinctiveness Conflict Risk

The narrow 'quantitative trading strategies' niche with concrete backtest/evaluate triggers is clearly distinguishable from other skills with minimal conflict risk.

5 / 5

Total

15

/

20

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

frontmatter_unknown_keys

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

Warning

relative_links

Relative link issues: 1 missing, 1 suspicious

Warning

Total

14

/

16

Passed

Repository
HKUDS/Vibe-Trading
Reviewed

Table of Contents

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