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quant-analyst

Build financial models, backtest trading strategies, and analyze market data. Implements risk metrics, portfolio optimization, and statistical arbitrage.

Quality

60%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/quant-analyst/SKILL.md

The canonical home for this skill is quant-analyst in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

36%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 presents a well-organized overview of the quant-analyst domain, but it functions mostly as a topic outline: guidance is principle-level with no executable content, workflow steps lack definition and validation checkpoints, and its one progressive-disclosure pointer targets a nonexistent file. Combined with circular use-when boilerplate, the skill needs concrete detail (or a real playbook file) to be genuinely actionable.

Suggestions

Fix or remove the dangling reference to 'resources/implementation-playbook.md' — no such file or directory exists in the bundle; either create it (e.g., under references/) or drop the pointer.

Add at least one executable artifact, e.g. a vectorized pandas backtest snippet with transaction costs/slippage, or a concrete step-by-step procedure with validation checkpoints (train/test split, lookahead-bias check, out-of-sample verification).

Delete the circular 'Use this skill when / Do not use this skill when' boilerplate and generic Instructions bullets, replacing them with domain-specific guidance Claude does not already know (e.g., data-source pitfalls, survivorship-bias checks, specific library conventions).

DimensionReasoningScore

Conciseness

The Focus Areas, Approach, and Output sections are dense and non-padded, but roughly a third of the body is circular boilerplate ('Working on quant analyst tasks or workflows', 'Needing guidance, best practices, or checklists') and generic process advice Claude already knows ('Clarify goals, constraints, and required inputs'), so it is mostly efficient with unnecessary content that could be tightened rather than noticeably verbose.

3 / 5

Actionability

Guidance is high-level throughout: 'Use pandas, numpy, and scipy' names tools, and 'Robust backtesting with transaction costs and slippage' states a principle, but there is no code, command, or concrete procedure anywhere, and the playbook that would carry the details ('resources/implementation-playbook.md') does not exist, leaving only minimal concrete guidance with missing execution steps.

2 / 5

Workflow Clarity

The Approach section lists a rough five-item ordering (data quality, backtesting, risk-adjusted returns, out-of-sample testing, research/production separation), but the items are principles rather than defined steps, and validation checkpoints are entirely absent, matching a rough sequence with many gaps and no validation.

2 / 5

Progressive Disclosure

Sections are clearly organized and the single external reference is one level deep and explicitly signaled ('If detailed examples are required, open resources/implementation-playbook.md'), but that reference is a dead end — no resources/ or references/ directory exists anywhere in the bundle — so navigation falls short of good structure with only minor gaps.

3 / 5

Total

10

/

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.

A solidly specific, third-person description that clearly conveys what the skill does, anchored in a distinct domain. Its main weakness is the complete absence of 'when to use' trigger guidance, which caps completeness and slightly raises conflict risk since triggering relies purely on keyword matching.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user asks to backtest a trading strategy, optimize a portfolio, compute risk metrics (VaR, Sharpe, drawdown), or build a quant model.'

Include natural synonyms and specifics users actually say, such as 'quant', 'VaR', 'Sharpe ratio', and 'pairs trading', to broaden keyword coverage.

Tighten the broad verbs ('Build financial models', 'analyze market data') into more granular actions like 'fit time-series forecasts' or 'ingest and clean OHLCV market data'.

DimensionReasoningScore

Specificity

Concrete actions like 'backtest trading strategies' and 'Implements risk metrics, portfolio optimization, and statistical arbitrage' name specific capabilities, but 'Build financial models' and 'analyze market data' remain broad strokes, leaving minor gaps in coverage rather than the comprehensive, granular action list of a 5.

4 / 5

Completeness

The 'what' is clearly stated (financial models, backtesting, risk metrics, portfolio optimization), but there is no 'Use when...' clause or equivalent explicit trigger guidance, which caps completeness at 3 per the judging guidelines.

3 / 5

Trigger Term Quality

Natural phrases users would say are present ('backtest trading strategies', 'portfolio optimization', 'statistical arbitrage'), but common variations and synonyms such as 'quant', 'VaR', 'Sharpe ratio', or 'pairs trading' are missing, so coverage is good rather than comprehensive.

4 / 5

Distinctiveness Conflict Risk

The quant-finance niche (statistical arbitrage, backtesting, portfolio optimization) is mostly distinct from other skills, though 'analyze market data' creates minor overlap risk with general data-analysis skills, keeping it below a 5.

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.

Validation — 15 / 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

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/AI-Agents-Safe-Coding-Skills-claude/skills/quant-analyst/SKILL.md

Reviewed

Table of Contents

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