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ZeroGEX — SPX/SPY/QQQ/NDX dealer positioning

Get delayed gamma levels

get_gamma_levels
Read-onlyIdempotent

Modeled options dealer-positioning levels for one underlying: gamma flip, call wall, put wall, max pain, same-day pin strike, and net dealer gamma at spot (whose sign is the regime). Use for "where is the gamma flip", "where are the walls", "is SPX in positive gamma". FREE DELAYED DATA — up to 15 minutes behind live, and the response states its own age; quote that age and never call these levels live. Not a price feed, not a forecast, and not a trade recommendation: it describes dealer positioning and says nothing on its own about direction. A null level means the modeled book does not support that level right now — report it as unavailable, never as zero.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesES and NQ have no options book of their own; their levels are the SPX and NDX option-derived levels already projected onto the futures price axis.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already mark it read-only, idempotent, and non-destructive, so the bar is lower; the description adds critical behavior: up to 15-minute delay, response states its own age, quote the age and never use live, and null levels mean unavailable rather than zero. No contradiction with annotations.

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?

Every sentence earns its place: purpose, use cases, data freshness, exclusions, and null-handling semantics. It is front-loaded with the core purpose and efficiently packs essential caveats without redundancy.

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

Completeness5/5

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

For a single-parameter tool with no output schema, the description covers the full set of returned levels, the delay and age behavior, the non-price-feed/forecast nature, and how to interpret nulls. An agent has enough to call it correctly and interpret results.

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?

There is only one parameter with 100% schema coverage, including an enum and a description of futures projection. The description adds general context ('one underlying') but does not add meaningful parameter-level detail beyond the schema, so the baseline 3 applies.

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 clearly identifies what the tool provides: modeled dealer-positioning levels (gamma flip, call wall, put wall, max pain, pin strike, net dealer gamma) for one underlying. The phrase 'for one underlying' distinguishes it from the market-wide sibling tool.

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 explicitly gives example queries such as 'where is the gamma flip' and 'is SPX in positive gamma', and states not to use it as a live price feed, forecast, or trade recommendation. It does not explicitly name the sibling alternative, but the 'one underlying' scope and 'never call live' instruction provide strong usage context.

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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