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Polygon-io MCP Server

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list_futures_market_statuses

Retrieve real-time market statuses for futures products on Polygon-io MCP Server. Filter by product code, set limits, and sort results for efficient market analysis.

Instructions

Get market statuses for futures products.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
paramsNo
product_codeNo
product_code_any_ofNo
sortNo
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states what the tool does ('Get market statuses'), without mentioning any behavioral traits such as whether it's a read-only operation, if it requires authentication, rate limits, pagination, or what the output format might be. For a tool with 5 parameters and no output schema, this lack of context is a significant 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?

The description is a single, efficient sentence: 'Get market statuses for futures products.' It is front-loaded and wastes no words, making it easy to parse. However, given the tool's complexity (5 parameters, no annotations), this brevity borders on under-specification rather than optimal conciseness.

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?

Given the tool's complexity (5 parameters, no annotations, no output schema), the description is incomplete. It fails to explain key aspects: what market statuses include, how parameters filter results, the return format, or behavioral constraints. With no output schema and low parameter documentation, the description should provide more context to help the agent use the tool effectively.

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%, meaning none of the 5 parameters (limit, params, product_code, product_code_any_of, sort) are documented in the schema. The description does not add any meaning beyond the schema—it doesn't explain what these parameters do, their expected values, or how they affect the query. With 0% coverage and no compensation in the description, the parameters remain largely opaque.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get market statuses for futures products' clearly states the action (get) and resource (market statuses for futures products), providing a basic understanding of the tool's function. However, it doesn't differentiate this tool from potential sibling tools like 'get_market_status' or 'get_futures_snapshot', which might offer similar or overlapping functionality. The purpose is clear but lacks specificity about scope or uniqueness.

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?

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'get_market_status' (which might cover broader markets) and 'get_futures_snapshot' (which could include status data), there's no indication of context, prerequisites, or exclusions. Usage is implied by the name but not explicitly stated, leaving the agent to guess based on tool names alone.

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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