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What does the equity curve look like? Seeded distribution of terminal outcomes (PAID $0.15)

v1_quant_monte_carlo

Simulates seeded Monte Carlo runs to project equity curves and terminal outcome distributions from trade data. Use it to assess strategy risk by modelling trade sequences alternative to one historical path.

Instructions

What does the equity curve look like? Seeded distribution of terminal outcomes (PAID $0.15)

Remote route: POST /v1/quant/monte-carlo (0.15 USD x402/base/usdc on eip155:8453).

Input Schema

NameRequiredDescriptionDefault
runsNo
seedNo
as_ofNo
tradesNo
trade_distributionNo

Output Schema

NameRequiredDescriptionDefault
statusNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.8/5.0
Behavior4/5

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

With annotations giving only readOnlyHint=false, openWorldHint=true and non-destructive/non-idempotent, the description adds genuinely useful behavioral context: this is a remote POST route that costs 0.15 USD via x402/base/USDC on eip155:8453, so the agent knows a paid network call is involved. It stops short of saying what the simulation costs in compute time or what happens on insufficient payment, which keeps it off a 5.

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

Conciseness3/5

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

It is short and front-loaded, but the first sentence simply restates the tool title verbatim, so one of only two sentences is wasted. The remaining route/payment sentence does earn its place. Net effect is brief but partly redundant rather than deliberately economical.

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

Completeness2/5

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

An output schema exists, so return values need not be described. Still, a five-parameter simulation tool with a nested object parameter, no annotations covering the simulation semantics, and 0% schema coverage requires far more than a title echo plus a payment line. The payment mechanics are covered; the actual invocation semantics are not.

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

Parameters2/5

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

Schema coverage is 0% across five parameters, and the description explains none of them — runs, seed, as_of, trades and the nested trade_distribution object are left entirely to bare titles. The word 'seeded' faintly gestures at the seed parameter but adds no meaning about what a seed does here or what the trade_distribution object must contain. This is exactly the case where the description needed to compensate and did not.

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

Purpose3/5

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

The line 'Seeded distribution of terminal outcomes' conveys that this is a stochastic simulation producing a distribution of ending equity values, which is the core resource. However, it is a noun phrase rather than a specific verb+resource statement and never names the closest siblings (v1_quant_risk_of_ruin, v1_quant_significance, v1_portfolio_risk) to distinguish itself. An agent has a rough idea but must infer the mechanism.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not-to-use guidance anywhere in the description. Nothing tells the agent what question this answers better than v1_quant_risk_of_ruin or a plain backtest, and no prerequisites or preconditions are stated. Only the payment cost is conveyed.

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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