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Grok Crypto Quant API

Validate an optimisation (free)

validate_optimize
Read-onlyIdempotent

Free: check optimize_strategy arguments and count grid combos before paying.

Input Schema

NameRequiredDescriptionDefault
endNoYYYY-MM-DD
feeNoFee per side (0.009 = 0.9%)
gridYesparam -> values to try
startNoYYYY-MM-DD
rank_byNorobust
slippageNoSlippage per side
strategyYes
universeNo
initial_capitalNoStarting capital in USD

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

The annotations already declare readOnly, idempotent, and non-destructive behavior, so the safety profile is covered. The description's genuinely additive contribution is the cost model ('Free' vs 'before paying') and the pre-flight combo counting, but it does not disclose what happens on invalid input, whether any network or data access occurs, or how combo limits are enforced.

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?

A single front-loaded sentence with zero filler: the cost signal comes first and the action second. It is arguably too terse for a 9-parameter nested tool, which slightly undercuts clarity, but nothing is wasted.

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

Completeness3/5

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

With an output schema present, return values need no explanation, but the description is thin for a tool with 9 parameters, nested objects, and a sibling contrast set. An agent does not learn what counts as a validation failure or what the combo count is used for beyond the implicit pre-pay check.

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 67%, so much of the parameter meaning is already structured data (universe modes, fee/slippage, start/end). The description only adds that 'grid' is enumerated as combos and that 'strategy' arguments are what is checked; it says nothing about rank_by, initial_capital, or fee/slippage beyond the schema.

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

Purpose4/5

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

The description states a specific verb ('check/validate') and resource ('optimize_strategy arguments'), plus a secondary function (counting grid combos), which distinguishes it from the sibling optimize_strategy it names. It stops short of saying what the validation result looks like, so the purpose is clear but not fully elaborated.

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

Usage Guidelines3/5

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

'before paying' implies the trigger condition — run this ahead of the paid optimize_strategy call — but the guidance remains implicit. There is no explicit statement of when not to use it or which sibling (validate_backtest, validate_universe) to pick for other argument sets.

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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