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backtesting-frameworks

Build robust backtesting systems for trading strategies with proper handling of look-ahead bias, survivorship bias, and transaction costs. Use when developing trading algorithms, validating strategies, or building backtesting infrastructure.

Quality

75%

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tessl review fix ./plugins/quantitative-trading/skills/backtesting-frameworks/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

51%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 excels at progressive disclosure — a concise overview with a verified, clearly signaled one-level-deep reference — but the overview itself is conceptual rather than operational: it explains biases and structures Claude already knows, duplicates the biases table in the Do's/Don'ts, and provides no executable workflow or validation checkpoints for building a backtest.

Suggestions

Replace or supplement the conceptual diagrams with a minimal executable quick-start (e.g., a short walk-forward data-split function or a concrete step sequence: acquire point-in-time data → include delisted securities → split → run → report costs), keeping the bulk in references/details.md.

Remove the redundancy between the biases table and the Do's/Don'ts section (e.g., "Use point-in-time data - Avoid look-ahead bias" restates the table's mitigation column); keep one consolidated checklist.

Add explicit validation checkpoints to the workflow, such as verifying each signal only uses data available at or before time t-1 and reconciling trade costs against a realistic cost model before reporting performance.

DimensionReasoningScore

Conciseness

The body is short but spends tokens explaining concepts Claude already knows — the biases table ("Using future information", "Only testing on survivors"), the train/validation/test ASCII diagram, and the walk-forward diagram — and the Do's/Don'ts bullets ("Use point-in-time data - Avoid look-ahead bias", "Don't ignore survivorship - Include delisted") largely restate the table's mitigation column. Mostly efficient with some unnecessary explanation and clear tightening opportunities, matching anchor 3; not 2 because the padding is limited rather than pervasive.

3 / 5

Actionability

The body names concrete techniques ("Point-in-time data", "Use delisted securities", walk-forward, Monte Carlo, pre-registration) but contains no executable code, commands, or step-level detail — the executable material lives entirely in references/details.md. This sits between anchor 2 (high-level hints only) and anchor 4 (mostly executable guidance): some concrete direction is given, but key execution details are missing from the body itself.

3 / 5

Workflow Clarity

Building a backtest is a multi-step process, but the body presents only a conceptual data-flow diagram (Training → Validation → Test) and walk-forward window pictures, not an operational sequence with steps to follow. There are no validation checkpoints (e.g., how to verify signals use only data available at time t), matching anchor 2's 'rough sequence present but many gaps; validation absent'; not 3 because the sequence shown is methodology structure rather than listed steps.

2 / 5

Progressive Disclosure

The body is a lean overview and points to a verified one-level-deep reference: "Detailed sections (starting with `## Implementation Patterns`) live in `references/details.md`. Read that file when the navigation summary above is insufficient." The referenced file exists and contains that exact section header, and the pointer includes an explicit read-when condition. This matches anchor 5: clear overview, well-signaled single-level reference, easy navigation.

5 / 5

Total

13

/

20

Passed

Description

87%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 strong description: third-person-style imperative voice, concrete what-and-when structure, and domain-specific trigger terms. Only minor keyword-coverage and capability-coverage gaps prevent top marks on specificity and trigger terms.

DimensionReasoningScore

Specificity

"Build robust backtesting systems for trading strategies" plus "proper handling of look-ahead bias, survivorship bias, and transaction costs" names several concrete capabilities (build systems, handle three named biases/costs), matching the 'several specific actions; minor gaps in coverage' anchor. Not 5 because coverage gaps exist (walk-forward analysis, performance metrics, Monte Carlo are not mentioned); not 3 because more than 1-2 concrete actions are listed.

4 / 5

Completeness

Explicitly answers both: what ("Build robust backtesting systems ... with proper handling of look-ahead bias, survivorship bias, and transaction costs") and when ("Use when developing trading algorithms, validating strategies, or building backtesting infrastructure") with concrete trigger phrases, matching the anchor-5 example structure. Neither component is vague or implied, so 4 would understate it.

5 / 5

Trigger Term Quality

Natural terms include "backtesting", "trading strategies", "trading algorithms", "validating strategies", and "backtesting infrastructure" — good keyword coverage matching the anchor-4 example style. Not 5 because common variations are missing (e.g., "backtest", "quant", "strategy validation", "walk-forward"); not 3 because the terms present are the ones users would naturally say.

4 / 5

Distinctiveness Conflict Risk

"Backtesting" for "trading strategies/algorithms" is a clear niche with distinct triggers and minimal conflict risk against other skills; the trigger terms (backtesting, trading algorithms, strategy validation) are domain-specific. Not 4 because no meaningful overlap exists with adjacent skills — the vocabulary is unambiguously quantitative-finance.

5 / 5

Total

18

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

wshobson/agents

Path

plugins/quantitative-trading/skills/backtesting-frameworks/SKILL.md

Reviewed

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