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biranjan01
by biranjan01

strategy_payoff

Calculate expiry payoff and probability for multi-leg option strategies using legs, spot, days to expiry, and implied volatility.

Instructions

Payoff analysis for a multi-leg option strategy at expiry.

Args: legs: list of {strike, right ('C'/'P'), qty (+ long / - short), premium, lot_size?} spot: current underlying price t_days: calendar days to expiry iv: annualized IV for probability estimate (decimal) lot_size: shares per contract (e.g. 6750 for CANBK), or use per-leg lot_size

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ivNo
legsYes
spotYes
t_daysNo
lot_sizeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden; it does disclose meaningful behavior — the analysis is expiry-only, and iv drives a probability estimate rather than a valuation. However it says nothing about output shape (payoff curve vs. scalar), whether it is a pure computation with no side effects, or any rate/limit characteristics.

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 scope sentence is front-loaded, and the Args list is compact and scannable, with the critical sign convention given inline in parentheses. Slightly information-dense but no filler sentences.

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?

For a 5-parameter analytical tool with no annotations and no output schema, the input side is covered well, but the description never says what the tool returns (payoff at expiry per spot? breakeven? probability?) or in what units, leaving the agent unable to anticipate the result.

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

Parameters5/5

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

Schema description coverage is 0%, so the embedded Args block does all the work: it defines each leg field (strike, right 'C'/'P', qty signed + long / - short, premium, optional per-leg lot_size) plus units for spot, calendar days for t_days, and decimal annualized IV. This resolves ambiguities the bare schema (array of additionalProperties objects) leaves completely open.

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 first sentence gives a specific verb+resource+scope: payoff analysis for a multi-leg option strategy, explicitly at expiry. It is distinguishable from max_pain and greeks by the 'payoff at expiry' framing, though it never explicitly contrasts itself with analyze_position, which sounds like the nearest sibling.

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 guidance, no prerequisites (e.g. whether live market data is needed), and no mention of when to prefer analyze_position, greeks, or max_pain instead. The 'at expiry' scope is stated but the agent must infer when this tool is the right choice.

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