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Foresea Forecasting

foresea_optimize_portfolio

Calculate optimal mathematical Fractional Kelly capital allocations and position sizes across live Grade A/B prediction market opportunities.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
min_edgeNo
bankroll_usdNo
kelly_fractionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description must carry the full burden. It clearly indicates a calculation (non-destructive) but does not disclose any side effects, dependencies on live data, or limitations. The phrase 'Grade A/B' hints at filtering criteria but adds no behavior beyond the verb 'Calculate.' It is not misleading but lacks depth.

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 a single, front-loaded sentence that efficiently conveys the core action and scope. While it lacks parameter details, it is appropriately concise with no redundancy or filler.

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?

The description provides the primary purpose but omits necessary context for a portfolio optimization tool with three parameters and no annotations. It does not explain how the parameters interact, what an optimal allocation entails, or any constraints. Given the tool's complexity and the sparse schema, the description is insufficient for a new agent to use it correctly.

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

Parameters1/5

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

Schema description coverage is 0%, and the description provides no meaning for 'min_edge,' 'bankroll_usd,' or 'kelly_fraction.' The term 'Fractional Kelly' hints at kelly_fraction but does not explain any parameter. The description fails to compensate for the undocumented schema.

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 states a specific verb ('Calculate') and a clear resource ('optimal mathematical Fractional Kelly capital allocations and position sizes') with scope ('across live Grade A/B prediction market opportunities'). It clearly distinguishes from sibling tools that focus on analysis, scanning, or data retrieval.

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?

Usage is implied by the phrase 'across live Grade A/B prediction market opportunities,' suggesting it is for active markets, but there is no explicit guidance on when to use this tool versus alternatives, no exclusions, and no mention of prerequisites or sequencing with other tools.

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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