Skip to main content
Glama
malav-majmudar

NFL Data MCP

list_stat_fields

Read-onlyIdempotent

Retrieve valid statistic field names for player or team leader queries by entity type, season, and unit.

Instructions

List valid factual statistic names for player/team leader and stat queries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
unitYes
seasonYes
entity_typeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description's 'List' aligns. It adds the context of returning valid statistic names but does not disclose additional behaviors like error handling or output structure, which is partially mitigated by the existence of an output schema.

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?

The description is a single, concise sentence that immediately communicates the tool's purpose with no unnecessary words. It is front-loaded and efficient.

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 three required parameters with no schema descriptions, the tool needs more explanation about parameter usage and allowed values. While the output schema exists, the description fails to provide sufficient context for correct invocation, making it incomplete.

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

Parameters1/5

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

Schema description coverage is 0%, and the description does not explain the three parameters (unit, season, entity_type). For instance, valid values for 'entity_type' (e.g., player or team) are not mentioned, leaving the agent without necessary context to invoke the tool correctly.

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 states the verb 'List' and the resource 'valid factual statistic names', specifying the scope for player/team leader and stat queries. This distinguishes the tool from siblings like 'get_stat_leaders' or 'find_stat_seasons' which perform different operations.

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?

No guidance is provided on when to use this tool versus alternatives, such as 'find_stat_seasons' or 'get_stat_leaders'. The context implicitly suggests it as a prerequisite but lacks explicit when-to-use or when-not-to-use instructions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/malav-majmudar/nfl-data-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server