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How much money can this strategy actually carry? Capacity with the binding constraint and the degradation curve (PAID $1

v1_strategy_capacity

Calculate how much capital a trading strategy can carry, identify the binding capacity constraint, and model performance degradation as capital scales.

Instructions

How much money can this strategy actually carry? Capacity with the binding constraint and the degradation curve (PAID $10.00)

Remote route: POST /v1/strategy/capacity (10.00 USD x402/base/usdc on eip155:8453).

Input Schema

NameRequiredDescriptionDefault
as_ofNo
marketNo
capitalNo
strategyNo

Output Schema

NameRequiredDescriptionDefault
statusNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, idempotentHint=false and openWorldHint=true; the description adds genuinely useful context by disclosing the remote route and the $10.00 x402/USDC payment, which explains the non-idempotent, costly nature of each call. It does not explain what happens when the market/capital/strategy blocks are omitted (all four parameters are optional), so the behavioral picture remains incomplete.

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?

Two tight sentences, front-loaded with the core question, followed by the delivery facts and payment route. No filler, though given the tool's complexity the brevity borders on under-specification rather than efficiency.

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?

For a tool with four nested-object parameter groups, zero property-level schema documentation and no required fields, the description is too thin: it never indicates which inputs actually drive the capacity estimate or how missing blocks are defaulted. The existence of an output schema excuses it from describing return values, but the input side is left to guesswork.

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 description coverage is 0% and the description contributes nothing about the four parameters: it never says that market (ADV, spread, sigma, impact coefficient), capital (AUM, risk per trade, cost budget) and strategy (R:R, win rate, trades per month) are the inputs, nor which are effectively required. The only help comes from the schema's own nested-object descriptions, so the description fails to compensate for the coverage gap.

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?

Names a specific deliverable: capacity sizing for a strategy, including the binding constraint and the degradation curve. That is far more concrete than a generic 'risk' tool and distinguishes it in spirit from siblings like v1_portfolio_risk or v1_quant_risk_of_ruin, though no sibling is named explicitly.

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?

No when-to-use / when-not-to-use guidance and no named alternative among the many sibling risk and strategy tools. The only usage signal is the $10.00 price, which implicitly tells the agent this is a paid call worth preflighting, but the agent must infer the scenario itself.

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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