strategy-generate

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

Quality

64%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

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/strategy-generate/SKILL.md

Quality

Content

70%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 a dense, actionable spec with an excellent sequenced workflow and validation/feedback loops, but it loses points for redundancy across the normalization/crypto sections and for relying on bundle files (examples.md) that do not exist. Splitting reference material into the missing files would lift both conciseness and progressive disclosure.

Suggestions

Create the referenced examples.md (or remove the dead link) so the example call sequence promised in 'Supporting Files' actually exists.

Deduplicate the instrument-code normalization rules — keep them in the 'Market Detection and Data Sources' table and reference it from the crypto notes rather than restating.

Move the full config.json field reference and the Review Criteria / Bug Categories detail into a separate reference file, keeping SKILL.md as an overview with one-level-deep links.

Dimension	Reasoning	Score
Conciseness	Mostly efficient and assumes Claude's competence, but instrument-normalization rules and crypto notes are restated across the 'Instrument Code Normalization', 'Cryptocurrency Notes', and 'Market Detection' sections, which could be consolidated.	3 / 5
Actionability	Provides a concrete SignalEngine contract with full signature/docstring, an exact config.json schema, regex patterns, and a syntax-check command; the gap is the referenced examples.md, which is absent, so common-case copy-paste examples are missing.	4 / 5
Workflow Clarity	A clear 7-step workflow opens the skill, with an explicit syntax-check validation step and an edit -> backtest -> re-evaluate feedback loop, plus a self-check Quality Checklist.	5 / 5
Progressive Disclosure	Sections are well-organized, but the only external reference (examples.md) and the cross-market-strategy SKILL link are broken/absent, and reference material like the full config-field docs and review criteria is inlined rather than split into reference files.	3 / 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 through concrete verbs but omits any 'Use when' trigger guidance, which is the main weakness. Trigger-term coverage is decent but lacks synonyms. It is a solid, mostly distinct description that needs an explicit usage clause to score higher.

Suggestions

Add a 'Use when...' clause naming natural triggers, e.g. 'Use when the user wants to build, backtest, or optimize a quantitative/algorithmic trading strategy.'

Include synonyms users actually say — 'quant strategy', 'algorithmic trading', 'backtesting a strategy' — to broaden trigger coverage.

Tighten the action list with one concrete sub-capability each (e.g. '...backtest them over historical data and evaluate Sharpe/drawdown') to push specificity toward 5.

Dimension	Reasoning	Score
Specificity	Lists several concrete actions ('Create, modify, and optimize... then backtest and evaluate') tied to a named domain (quantitative trading strategies); falls short of 5 because the actions are generic verbs without sub-capabilities.	4 / 5
Completeness	The 'what' is clear (create/modify/optimize/backtest/evaluate strategies), but there is no 'Use when...' clause or equivalent trigger guidance, which caps completeness at 3 per the rubric.	3 / 5
Trigger Term Quality	'quantitative trading strategies' and 'backtest' are relevant natural terms, but synonyms like 'quant strategy', 'algorithmic trading', or file/extension triggers are missing, so coverage is partial.	3 / 5
Distinctiveness Conflict Risk	The quantitative-trading + backtest niche is clearly distinguishable with minimal conflict risk, though it could overlap with adjacent finance/trading skills.	4 / 5
	Total	14 / 20 Passed

Validation

87%

Warnings & errors only

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

Validation — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
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: charliedream1/ai_quant_trade
Path: a_全网优秀资源/10_大模型/07_skill包/vibe_trading_skills/strategy-generate/SKILL.md
Commit: 6565e03

Reviewed: 8 days ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.