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backtest

Run cross-sectional strategy simulations with point-in-time data, transaction costs, and purged cross-validation for deflated Sharpe metrics.

Instructions

Run a cross-sectional backtest. Point-in-time and costed by construction.

At each rebalance the engine sees only data knowable strictly before that date. Costs are always charged on turnover; there is no zero-cost mode.

The validation block leads with purged cross-validation across every held-out combination of blocks. Its multiple_testing sub-block carries the deflated Sharpe and the count of specs run since the last reset. That correction assumes the specs were attempts at one question; if this run starts an unrelated line of enquiry, pass reset_trials=True to zero the count first.

Signals: momentum_12_1, momentum_6_1, reversal_1m, low_volatility, trend_200d.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNo
startNo
signalNomomentum_12_1
cost_bpsNo
long_pctNo
universeYes
rebalanceNoME
short_pctNo
reset_trialsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does an excellent job: it discloses that the engine only sees point-in-time data, costs are charged on turnover, validation is purged cross-validation, and multiple testing correction is applied. It also explains the reset_trials behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with front-loaded purpose, followed by key behavioral details and parameter-specific notes. It is a bit longer than minimal but every sentence adds useful information, so it earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex tool with 9 parameters, the description covers the core methodology, safety/cost behavior, validation scheme, and signal choices. Output schema exists for return values, so this is adequate. Minor gaps remain on parameter details, but overall it is fairly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It enumerates valid signal values (momentum_12_1, etc.) and explains reset_trials, but does not clarify start/end, universe, long_pct/short_pct, or rebalance parameters. This is partial compensation given the 9 parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Run a cross-sectional backtest', which is a specific verb+resource that clearly identifies the tool's function. It distinguishes from siblings like 'benchmark' by emphasizing the cross-sectional, point-in-time, and costed nature.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides clear context: costs are always charged, no zero-cost mode, and a conditional guideline for reset_trials when starting an unrelated enquiry. However, it does not explicitly compare to alternatives or state when NOT to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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