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hplin

tastytrade-research-mcp

by hplin

tastytrade_create_spx_spread_backtest

Create historical SPX spread backtests using relative leg selectors to model option strategies, while double diagonals require exact simulation.

Instructions

Create an aggregate SPX spread Backtester job when the structure can be represented faithfully enough by relative leg selectors. Double diagonals remain exact-simulation only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden, and it does meaningful work by revealing that this is an aggregate/approximate backtest rather than exact simulation, and that double diagonals are excluded. It does not fully describe the job lifecycle or return behavior, but it discloses the most important behavioral limitation.

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

Conciseness5/5

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

Two short sentences with no filler. The primary use condition is front-loaded, and the exclusion is stated immediately after. Every sentence contributes selection or invocation guidance.

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?

The description is strong for tool selection but weaker for invocation and post-creation expectations. There is no output schema, no annotations, and a complex nested request object, so the description should say more about what happens after the job is created and how results are retrieved. The double-diagonal guardrail is helpful but not sufficient for full contextual completeness.

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. The phrase 'relative leg selectors' adds meaning to the backtest_selector concept inside the request, and the aggregate-vs-exact distinction helps interpret the family field. However, it does not explain required fields like intended_price, price_effect, entry_at, or exit_at, leaving a meaningful gap.

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 names a specific action ('Create'), a specific resource ('aggregate SPX spread Backtester job'), and the key mechanism ('relative leg selectors'). It also distinguishes this tool from exact-simulation tools by declaring that double diagonals are not supported here.

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 gives a clear when-to-use condition: use this when the structure is faithfully representable by relative leg selectors. It also gives an explicit when-not: double diagonals are exact-simulation only. However, it does not name the exact-simulation sibling tool directly, and 'faithfully enough' is somewhat subjective.

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