Option Desk

Strategy payoff plot

option_strategy_plot

Read-onlyIdempotent

Show an option-strategy payoff as an opaque PNG in the conversation. Any structure in the engine playbook can be built on the SYNTH sample chain. A market ticker requires user-supplied chain data. Do not start a localhost dashboard.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "option_strategy_plot"
  }
}

Input Schema

Name	Required	Default
`rate`	No
`expiry`	No
`symbol`	No	SYNTH
`strategy`	No	iron_condor
`data_source`	No
`source_data`	No
`source_text`	No
`source_format`	No
`dividend_yield`	No
`rights_confirmed`	No

Output Schema

Name	Required	Description
`units`	No
`expiry`	Yes	Option expiry, when available.
`images`	No	The returned images, for the inline plot app.
`warning`	Yes	Data and financial-risk warning.
`strategy`	Yes	Requested strategy for a payoff plot, when applicable.
`data_mode`	Yes	Whether the figures are synthetic or user supplied.
`plot_types`	Yes	Plot names in the same order as the image content.
`underlying`	Yes	Underlying shown by the plots.
`captured_at`	Yes	Snapshot or fixture timestamp, when available.
`data_source`	Yes	Named source used for the figures.
`diagnostics`	No
`expiry_note`	No	Set when the requested expiry is not the one the figures are for.
`image_count`	Yes	Number of returned PNG images.
`strategy_records`	No	Exact plotted engine records. Use these for tables; do not infer values from images.

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 11, 2026

TDQS

A3.5/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds genuinely new context: the return is an opaque PNG rendered inline, and the agent must not spin up a localhost dashboard. It omits that rights_confirmed defaults to false and appears to gate real-ticker data, which is a meaningful behavioral gap.

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?

Four short sentences, front-loaded with the purpose, and each adds a distinct constraint rather than restating the name. The localhost-dashboard sentence is oddly specific but functions as a real guardrail, so it earns its place.

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

Completeness4/5

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

For a zero-required-parameter tool with an output schema and full annotation coverage, the description covers purpose, data sourcing, and the no-dashboard constraint adequately. The unresolved gap is parameter meaning: with 10 undocumented parameters and 0% schema coverage, an agent cannot tell what rights_confirmed or source_format require.

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% across 10 parameters, so the description carries the full burden. It only indirectly hints at symbol (SYNTH default) and data_source/source_data (user-supplied chain data); it says nothing about rate, expiry, strategy values, source_format, dividend_yield, or rights_confirmed.

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?

States a specific verb and resource ('Show an option-strategy payoff') plus the output form ('opaque PNG in the conversation'), which separates it from pure data tools like option_chain_snapshot. It does not explicitly distinguish itself from the closer siblings option_plots and option_plots_from_snapshot, so the differentiation is only partial.

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?

Gives conditional context: SYNTH sample chain works for any playbook structure, while a real market ticker requires user-supplied chain data, and it explicitly says not to start a localhost dashboard. However it never states when to pick this tool over option_plots or option_plots_from_snapshot, leaving the main selection decision implicit.

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

All Option Desk tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?